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Data Engineer

London – 4-5 Days per Week in Office

£70,000-£90,000 + Equity + Benefits

We’re working with a rapidly growing, YC-backed healthcare AI startup building a market-leading data platform used by pharmaceutical, biotech and healthcare organisations.

The Opportunity

This is not a role where you’ll maintain legacy pipelines or work on a small corner of an established platform. The team is specifically looking for engineers who have experience taking products, platforms or major features from 0-1.

You should be able to demonstrate that you’ve:

• Built something from scratch rather than simply maintained existing systems
• Worked through ambiguity with limited requirements
• Designed architecture and made key technical decisions
• Owned delivery from idea through to production
• Worked closely with product teams, users or founders to shape solutions
• Shipped products that generated real business value

The successful candidate will help build and scale the core data infrastructure powering the company’s platform, taking ownership of projects from raw data acquisition all the way through to production-ready products.

What You’ll Be Doing

• Building scalable ETL/ELT pipelines using Python and SQL
• Designing and developing data ingestion frameworks
• Working with large, complex and often messy datasets
• Leveraging AI and LLM technologies for extraction, classification and enrichment
• Building data products that directly support customers
• Designing schemas, entity resolution and data quality processes
• Collaborating closely with engineering, product and leadership teams
• Taking projects from concept through to production deployment

What We’re Looking For

Essential

• Strong Python and SQL skills
• Experience building production-grade data pipelines
• Proven ownership of end-to-end engineering projects
• Experience building products, platforms or major capabilities from 0-1
• Ability to operate independently in a fast-moving environment
• Strong problem-solving skills and technical foundations

Highly Desirable

• Startup or scale-up experience
• Experience working directly with founders or product teams
• LLMs, AI tooling or prompt engineering exposure
• Data acquisition, scraping or ingestion experience
• Snowflake, Databricks or modern cloud data platforms
• Experience turning technical outputs into customer-facing products

The Person

We’re looking for someone who enjoys building rather than maintaining.

You’ll thrive here if you get energy from starting with a problem, designing a solution and seeing it through to production. The ideal candidate will have a track record of operating in environments where ownership is high, processes are light, and shipping quickly matters. Years of experience are less important than evidence of what you’ve actually built.

Package

• £70,000-£90,000 base salary
• Opportunity to join a high-growth, YC-backed startup
• Significant ownership and autonomy
• Chance to help shape the future of a data-first AI product
• 4-5 days per week in the London office

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Data Engineer
London (1 day per month in office)
Up to £60,000 + Benefits

This is an excellent opportunity for a Data Engineer to join a growing Business Intelligence function and play a key role in shaping analytics and reporting capability across the business. You’ll work with modern data technologies, build scalable solutions, and help drive data-led decision making across the organisation.
The Company
They are a growing organisation investing heavily in their data and analytics capabilities to support business performance and strategic decision making. Their Business Intelligence team is focused on delivering high-quality, scalable data solutions that empower stakeholders with reliable insights. This is a collaborative environment where data plays a central role in driving business success.
The Role
You will:

• Build and maintain reliable data pipelines that integrate, clean, and structure data from multiple sources.
• Design and optimise data models to support reporting and analytics requirements.
• Create scalable data assets that enable business teams to generate actionable insights.
• Implement data quality controls, validation processes, and error handling to ensure data integrity.
• Work closely with stakeholders to understand requirements and deliver impactful data solutions.
• Contribute to the continued development of reporting and analytics capabilities across the business.

Your Skills & Experience

• Strong commercial experience in data engineering and data integration.
• Hands-on experience with DBT.
• Advanced SQL skills for data transformation and automation.
• Experience working with Snowflake and cloud-based data platforms.
• Strong understanding of data modelling and data warehousing concepts.
• Experience building dashboards and reports using Power BI.
• Knowledge of data quality assurance, validation processes, and troubleshooting.
• Strong communication skills with the ability to engage technical and non-technical stakeholders.

What They Offer

• Salary up to £60,000.
• Comprehensive benefits package.
• Hybrid working with just one day per month in the London office.
• Opportunity to work with modern data technologies in a growing data function.
• Clear opportunities for career progression and professional development.
• The chance to shape data solutions that deliver measurable business impact.

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To Apply for this Job Click Here

Director of Product Engineering
London | Up to £150,000
Hybrid (4 Days per Week in Office)

This is an exceptional opportunity for a senior technology leader to shape the future of a growing Data & AI business. You’ll play a pivotal role in building and scaling a high-performing Product Engineering function, driving the development of innovative data-driven products used by enterprise clients.

The Company
This organisation develops sophisticated products that combine customer data, advanced analytics, AI, and software applications to help businesses make better commercial decisions. With an established client base and ambitious growth plans, they are investing heavily in their engineering capability to create scalable, repeatable, and reliable product solutions. Their culture values technical excellence, innovation, and continuous improvement, providing a strong platform for senior leaders to make a meaningful impact.

The Role
You will:

• Lead multidisciplinary teams across Data Science, Data Engineering, Platform Engineering, and Application Development.
• Drive technical strategy, architecture, and engineering excellence across the product portfolio.
• Own the end-to-end delivery of scalable, production-ready data and AI solutions.
• Provide hands-on technical leadership through architecture reviews, problem-solving, technical validation, and code reviews where appropriate.
• Build strong engineering practices across software development, data platforms, testing, deployment, and operational support.
• Develop and mentor technical leaders, creating a culture of accountability, learning, and continuous improvement.
• Champion the adoption of AI-enabled development practices to improve quality and delivery speed.
• Collaborate with senior stakeholders and enterprise clients to provide technical leadership on complex initiatives.
• Influence the evolution of cloud, data, and application platforms, ensuring they support future growth.

Your Skills & Experience

• Strong experience leading engineering, data, and analytics teams within a product-led environment.
• Commercial expertise across software engineering, data engineering, and data science functions.
• Hands-on knowledge of cloud technologies, particularly Azure and modern data platforms.
• Strong understanding of Python, SQL, data architecture, distributed systems, and production environments.
• Experience delivering machine learning, AI, or advanced analytics solutions into production.
• Ability to balance strategic leadership with technical involvement in complex projects.
• Strong stakeholder management skills with experience engaging both technical and executive audiences.
• Passion for building teams, improving engineering standards, and driving organisational change.

What They Offer

• Salary up to £150,000.
• Hybrid working with four days per week in their London office.
• Significant influence over technology strategy, architecture, and product direction.
• Opportunity to build and scale a high-performing Product Engineering organisation.
• Exposure to cutting-edge AI, machine learning, and data-driven product development.
• Excellent career progression within a rapidly growing business.

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PRINCIPAL CONSULTANT, CREDIT RISK & ANALYTICS

LONDON | £90,000 – £120,000 + BONUS + BENEFITS

This is an exciting opportunity to join a specialist financial services consultancy in a senior leadership role. You’ll lead high-profile credit risk and analytics engagements and play a key role in growing both the team and the wider practice.

THE COMPANY

They are an established consultancy specialising in risk, analytics, and data-driven decision making across financial services. Working with a broad range of lending and financial services clients, they deliver high-impact projects spanning risk modelling, portfolio analytics, forecasting, and business strategy.

THE ROLE

* Gain exposure with key stakeholders while also retaining ownership of project delivery

* Manage projects end to end across credit risk modelling, forecasting, portfolio analytics, and strategy development

* Opportunity to contribute to overall business management

* Mentor and develop consultants and analysts across the team

* Contribute to the growth and strategic direction of the wider business

YOUR SKILLS & EXPERIENCE

* Strong commercial experience within credit risk analytics, consumer lending, or SME lending

* Deep expertise in credit risk modelling, customer analytics, forecasting, portfolio analysis, or risk strategy

* Proven experience managing analytical projects and leading teams

* Strong technical skills in SQL, SAS, or Python

– Excellent communication skills with the ability to translate analytical insights into commercial recommendations

* Previous consulting experience is beneficial but not essential

WHAT THEY OFFER

* £90,000 – £120,000 base salary depending on experience

* Annual bonus scheme

* Contributory pension

* Hybrid working model

* Exposure to a diverse range of high-impact client projects

* Clear progression opportunities within a growing consultancy

* Collaborative and supportive culture with a strong focus on professional development

HOW TO APPLY

Please register your interest by sending your CV through the Apply link.

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Staff Data Scientist, Finance – Consumption Forecasting

Location: San Francisco or New York | Hybrid (3 days per week in office)

Salary: $240-300k base + bonus + equity (RSUs)

This is a rare chance to own forecasting infrastructure at the center of a high-growth, consumption-based developer platform, one that powers some of the world’s most dynamic applications and scales with every developer and enterprise building on it.

As a consumption-based business, forecasting usage across compute, bandwidth, edge, and storage isn’t a support function. It’s foundational to how we plan infrastructure, revenue, and long-term strategy. This role exists to lead that work at the highest level.

What you’ll own

This is a senior individual contributor role with organization-wide impact. You’ll define forecasting methodology, build systems that scale with a rapidly growing platform, and sit at the intersection of Finance, Infrastructure, Product, and GTM with direct visibility to executive leadership.

• Own production revenue forecasting end-to-end: model development, backtesting, deployment, monitoring, and iteration from first principles to live system
• Build forecasting systems that account for usage-based pricing dynamics, consumption patterns, and customer lifecycle across the platform, built for how this business actually works, not retrofitted SaaS models
• Design hierarchical forecasting models across account, cohort, segment, and global aggregate levels, covering operational, quarterly, and long-range planning cycles
• Establish backtesting, monitoring, and explainability standards that make forecast accuracy transparent and defensible
• Build scenario simulation frameworks to evaluate pricing changes, packaging adjustments, and product launches
• Partner with Finance on board-level reporting, with Infrastructure Engineering on capacity planning, and with Product and GTM on adoption curves and usage drivers
• Set forecasting best practices across the broader Data organization

What we’re looking for

• 7+ years in data science, quantitative analytics, or applied statistics at senior or staff level
• Deep expertise in time-series forecasting and statistical modelling in a usage-based or SaaS environment
• Proven track record building and productionizing ML systems at scale
• Strong Python and SQL, with experience on large-scale usage and billing datasets
• Familiarity with probabilistic modelling, hierarchical forecasting, and causal inference
• Experience partnering with Finance or executive leadership on planning cycles
• Comfortable operating autonomously in fast-moving, ambiguous environments

Nice to have

• Background in cloud infrastructure, developer tools, or consumption-based revenue models
• Familiarity with modern data stacks: Snowflake, Delta Lake, dbt, Airflow
• Prior technical mentorship or informal leadership experience

To Apply for this Job Click Here

To Apply for this Job Click Here

Principal Software Engineer – Data Platform

San Francisco, CA (Remote Eligible – US Only)

$230K-$280K base + equity

Are you ready to lead the design and build of a world-class data platform from the ground up?

A high-growth, product-led tech company is looking for a Principal Software Engineer to lead the build-out of a modern, scalable data platform from the ground up. If you’re excited about solving massive data challenges and shaping the infrastructure that supports real-time analytics and AI/ML at scale, this role is for you.

As the most senior technical IC on the Data Platform team, you’ll partner with leadership across Engineering, Product, Security, and Compliance to design a low-latency, cloud-native data architecture using best-in-class tools like Kafka, Iceberg, ClickHouse, Tinybird, and Snowflake.

Why this role?

• Join a growing Data Platform team
• Own the technical vision and architecture end-to-end
• Tackle petabyte-scale data challenges and real-time streaming use cases
• Work with a cutting-edge tech stack (Kafka, Iceberg, ClickHouse, Snowflake, etc.)
• Drive platform evolution to support AI/ML and company-wide analytics

What You’ll Do

• Design and build a next-gen data platform to power product and internal use cases
• Architect for batch + streaming, scalability, fault tolerance, and low latency
• Lead data modeling, warehousing, governance, and ingestion best practices
• Champion engineering excellence and mentor senior engineers
• Align technical decisions with long-term business strategy
• Optimize for performance, cost, and resiliency in a modern cloud environment

What We’re Looking For

• 8+ years of experience in data engineering or platform architecture
• 5+ years at the Principal Engineer level or equivalent
• Deep expertise with Kafka (and its ecosystem), streaming data systems
• Strong experience with ClickHouse, Iceberg, Snowflake, or similar tools
• Cloud-native architecture expertise (AWS, GCP, or Azure)
• Track record of designing data systems for compliance and governance
• Experience scaling systems to support petabyte-level workloads
• Excellent communication, collaboration, and leadership skills
• Bonus: Experience enabling AI/ML platforms or preparing for IPO-scale growth

To Apply for this Job Click Here

To Apply for this Job Click Here

Senior Data Engineer

San Francisco, CA

$180-240K base + equity

We’re partnered with one of the most recognized developer platforms in the world, trusted by engineering teams at OpenAI, Meta, Netflix, and Adobe, who are scaling their data platform and looking to hire a Senior Data Engineer to own the pipelines and foundations at the core of their data ecosystem.

You’ll own the full pipeline lifecycle, from ingestion architecture through to analytics-ready data, working closely with Data Platform Engineers and partnering with analysts and data scientists who depend on what you build every day.

What you’ll do

• Design and build scalable ingestion pipelines and orchestration frameworks across structured, semi-structured, and event-based sources
• Own reliability, observability, and performance across the full pipeline lifecycle from raw ingestion to analytics-ready delivery
• Build and maintain dbt transformation pipelines serving as the single source of truth across Finance, Product, GTM, and Engineering
• Ensure revenue and billing data meets the accuracy and auditability required for public company reporting, including SOX compliance
• Apply software engineering principles throughout: CI/CD, testing, observability, version control, and automation
• Enable self-serve analytics through semantic layer development, strong abstractions, and clear documentation
• Champion data quality and governance across classification, ownership, access policies, and data lifecycle management

What we’re looking for

• 5+ years in data engineering or a hybrid data/analytics engineering role, with a track record of owning pipelines end-to-end in high-growth or enterprise environments
• Advanced SQL and dbt (Core or Cloud), Snowflake or comparable cloud data warehouse, Python, and Airflow
• Experience with Kafka and streaming data systems, with working knowledge of ClickHouse, Iceberg, or similar technologies
• Experience with ingestion tools such as Fivetran, Airbyte, or Polytomic
• Cloud-native architecture experience across AWS, GCP, or Azure
• Exposure to designing data systems that meet compliance and governance requirements, including SOX or equivalent
• Strong communication and collaboration skills, with the ability to contribute as a technical voice across engineering and business stakeholders

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Staff GTM Data Scientist

Location: Remote

Salary: $190-220k base

We’re partnering with a fast-growing SaaS company to find a Staff Data Scientist for a senior, high-visibility role sitting at the heart of their product and go-to-market strategy. This isn’t a reporting role or a dashboard-builder position. It’s for someone who can drive a genuine shift toward data-driven decision making across the organization, and who has the technical depth and communication skills to bring leadership along with them.

What You’ll Be Doing

• Owning and advancing the company’s experimentation roadmap, focusing on high-leverage questions around customer workflows, churn risk, and long-term value
• Designing and analyzing complex A/B tests, multivariate experiments, and Bayesian methods to assess the real impact of product and business changes
• Applying causal inference techniques (DiD, synthetic control, propensity score matching, instrumental variables) where traditional RCTs aren’t feasible
• Building and governing a unified KPI framework that connects product health metrics to business outcomes
• Partnering with Data Engineering to build scalable, self-serve experimentation tooling and reusable analytical frameworks
• Translating complex statistical findings into clear, compelling narratives for VP and C-suite audiences
• Mentoring and training junior and mid-level data scientists on experimental design and causal modeling

What We’re Looking For

This is a senior individual contributor role reporting to the Director of GTM Data, acting as a strategic thought partner across Product, Marketing, Finance, and Engineering. The company is at an inflection point in how it uses data, and this person will be central to shaping that.

Essential:

• 6+ years in applied data science, economics, or product analytics
• Proven expertise in causal inference: DiD, PSM, instrumental variables, quasi-experimentation
• Deep experience in A/B testing methodology including sequential testing, CUPED, variance reduction, and network effects
• Advanced SQL and Python or R for statistical modeling
• Experience with Snowflake or similar cloud data warehouses
• Exceptional communication skills, comfortable presenting to and influencing C-suite stakeholders
• Demonstrated ability to drive change in organizations where experimentation culture is still maturing

Nice to have:

• Experience with dbt, Airflow, or Databricks
• Background in SaaS and product data science

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Senior Analytics Engineer

Location: Remote

Salary: $150-170k base

We’re partnering exclusively with a fast-growing SaaS company to find a Senior Analytics Engineer to join their data team. This is a high-impact, high-autonomy role sitting at the intersection of data engineering and analytics, perfect for someone who takes pride in building data foundations that the whole business relies on.

What You’ll Be Doing

• Designing and building dimensional data models in Snowflake that underpin analytics across the business
• Developing and optimising dbt models to turn raw source data into clean, trusted datasets
• Partnering with analysts and business stakeholders to translate their needs into scalable data solutions
• Implementing data quality checks and owning the reliability of analytics datasets
• Contributing to data governance including PII handling, metadata management, and documentation
• Supporting strategic analytics across customer journeys, revenue metrics, and product usage
• Mentoring junior team members and championing best practices

What We’re Looking For

The company runs a best-in-class modern data stack built around Snowflake, dbt, and Monte Carlo, with data flowing in from Salesforce, HubSpot, Recurly, and core product databases. The team is evolving toward an AI-enabled, domain-oriented data organisation, so there’s real scope to shape the architecture, not just maintain it.

Essential:

• 5+ years in analytics engineering, data engineering, or a similar data-focused role
• Expert-level SQL: complex queries, CTEs, window functions
• Strong hands-on dbt experience
• Snowflake (or equivalent cloud warehouse: BigQuery, Redshift)
• Solid understanding of dimensional modelling and data warehouse design patterns
• Experience with SaaS metrics: MRR, churn, CLV etc.
• Python for data work or automation
• Familiarity with data orchestration tools (Airflow / MWAA)
• Comfortable working remotely and cross-functionally with distributed teams

Nice to have:

• Experience with reverse ETL tools such as Hightouch
• Exposure to BI tools (Hex preferred)
• Understanding of data mesh or domain-oriented architecture concepts

To Apply for this Job Click Here

To Apply for this Job Click Here

Staff Growth Product Analyst

US Remote

$200-240k base + equity

About the Role:

We’re looking for a Staff Growth Product Analyst to drive impactful growth analytics for an innovative AI-driven development platform that’s transforming how developers create and deploy user interfaces. Leveraging cutting-edge AI technologies, this platform enables rapid prototyping and significantly accelerates product development, enhancing user growth, engagement, and overall developer experience.

Role Highlights:

• Deep dive into user behaviors, journeys, and growth funnels to uncover opportunities for enhanced engagement and acquisition.
• Generate actionable insights aimed at boosting critical growth metrics like DAU, MAU, and user retention.
• Design, execute, and analyze A/B tests to drive informed decision-making and product improvements.
• Influence strategic decision-making through rigorous data analysis and compelling recommendations.
• Collaborate cross-functionally with product managers, engineers, data scientists, and growth marketers to drive continuous product improvement and iteration.

Who You Are:

• You have 7+ years of proven expertise in growth and product analytics, ideally within early-stage or innovation-driven product environments.
• You’re adept at conducting thorough funnel analyses, spotting rapid experimentation opportunities, and recommending actionable product enhancements.
• You thrive on solving complex analytical problems with high energy and intellectual rigor.
• Experienced with modern data stack (e.g., Snowflake, dbt, Preset, Hashboard, Kafka, Fivetran, Omni, Hex, Sigma, SQL, Python).
• You have previous experience (or a strong interest) in working with AI or machine learning-driven products.

Ideal Fit: You’re a driven, collaborative analytics expert passionate about influencing groundbreaking products. Excited by high-paced, innovative environments, you’re motivated by measurable impact and shaping the future of developer-focused, AI-powered technologies.

To Apply for this Job Click Here

To Apply for this Job Click Here

Staff Data Platform Engineer

US Remote

$200-245k base + Equity

We’re working with a rapidly expanding consumer tech startup that recently raised $125M in Series D funding. As they continue to scale, they’re looking to hire a Staff Data Engineer to join their growing data team. If you have a strong foundation in software engineering, a collaborative mindset, and a passion for driving data strategy, this is the opportunity for you!

The Role:
As a Staff Data Engineer, you’ll be a crucial part of the team, ensuring data is accessible, reliable, and actionable across the company. Working alongside engineers, data scientists, and business teams, you’ll help build scalable data platforms that drive key business initiatives and enable data-driven decision-making.

What You’ll Do:

• Collaborate with engineering, data science, and business teams to understand data needs and implement effective solutions aligned with business objectives.
• Design and build scalable data infrastructure and pipelines to handle high volumes of data as the company grows.
• Lead the design and optimization of data architecture, ensuring it’s secure, high-performing, and scalable.
• Improve and streamline data pipelines to provide fast, reliable access to high-quality data.
• Contribute to the design of reporting frameworks and analytics tools that empower teams to make data-driven decisions.
• Work with security teams to ensure data privacy and compliance standards are met.
• Mentor junior engineers, share expertise, and promote best practices across the team.
• Stay updated on new technologies and suggest improvements to enhance processes and tool efficiency.

You’re a Great Fit If:

• You have 7+ years of experience in data engineering.
• You’ve worked at a leading consumer tech company known for engineering excellence.
• You’re an expert in SQL, Python, and data platform development.
• Nice-to-have: Familiarity with AWS, Kubernetes, Redshift, Athena, S3, and Airflow.
• You have hands-on experience with complex data infrastructures and optimizing data pipelines.
• You’ve led large-scale data projects that had a significant impact on your organization.
• You thrive in collaborative environments and have strong communication skills.
• You have an ownership mindset and take responsibility for delivering results.

To Apply for this Job Click Here

To Apply for this Job Click Here

Senior Analytics Engineer
Location: Los Angeles, CA (Hybrid)

Salary: $150-200k base

We’re partnering with a rapidly scaling, mission-focused advanced technology company operating at the intersection of AI, hardware, and large-scale systems. Their software platform aggregates and operationalizes complex, real-time data to power critical decision-making in high-stakes environments.

As the company continues to grow, they are hiring a Senior Analytics Engineer to help architect and scale the core data foundation of the business.

The Opportunity

You will design and implement the core data models that represent how the organization operates across functions such as Finance, Supply Chain, Manufacturing, People, and Operations. These models will power internal applications, workflows, and metrics used by leadership to run the business.

You’ll sit at the intersection of analytics, engineering, and operations, helping build a scalable “digital twin” of a fast-moving, technically complex organization.

What You’ll Do

• Define and develop domain-level data models that reflect real business operations
• Build secure, scalable, and extensible transformations and data pipelines
• Own ingestion and egress frameworks across multiple source systems
• Contribute to architectural decisions and roadmap direction for the data platform
• Partner cross-functionally with engineering, product, and operations stakeholders
• Translate ambiguous business questions into structured, production-grade data systems
• Drive adoption of self-serve data applications beyond traditional BI

What They’re Looking For

• 5+ years of experience in Analytics Engineering, Data Engineering, or highly technical analytics roles
• Advanced SQL skills and strong experience with Python or similar languages
• Demonstrated success building scalable, reusable data models in fast-paced environments
• Experience with modern data stack tools such as dbt, Redshift, and BI platforms; exposure to enterprise data platforms is a plus
• High degree of ownership and comfort operating autonomously
• Strong communication skills and ability to partner with non-technical stakeholders
• Ability to obtain and maintain a U.S. Secret security clearance

This is a high-impact opportunity to shape foundational data systems inside a company solving complex, real-world problems at scale. If you’re excited by building data applications that influence how an organization operates, click apply to learn more.

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