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Staff Data Analyst – GTM

Location: Remote
Salary: $200-250k

This fast-growing, Series C cloud platform company is at the forefront of technological innovation, delivering cutting-edge solutions that drive industry transformation. The organization is seeking a highly skilled Staff Data Analyst to lead Go-to-Market (GTM) analytics efforts, enabling strategic growth and turning complex datasets into actionable insights to optimize GTM performance and operational efficiency.

About the Role

This position is central to defining and implementing data strategies that empower GTM teams. By developing metrics, automating reporting, and delivering insightful analyses, the Staff Data Analyst will play a critical role in optimizing growth strategies and ensuring data-driven decision-making.

Key Responsibilities

• Define and implement key GTM metrics to evaluate performance and uncover growth opportunities.
• Conduct in-depth analysis of complex datasets to deliver actionable GTM insights.
• Collaborate with cross-functional teams to identify root causes, refine processes, and inform strategic initiatives.
• Automate reporting workflows and create interactive dashboards to support leadership decision-making.
• Build and enhance datasets for growth optimization and cost reduction initiatives.
• Develop data accessibility solutions, ensuring timely and structured access to insights for all stakeholders.
• Shape the GTM analytics roadmap, aligning data projects with broader organizational goals.

About You

• 6+ years in analytics roles, with expertise in SaaS and product-led growth (PLG) business models.
• Advanced proficiency in SQL and experience with tools such as Looker, Hashboard, or Omni. Familiarity with Python or R and statistical modeling.
• Demonstrated ability to interpret trends, conduct root cause analysis, and deliver data-driven recommendations that influence strategy.
• Strong ability to present complex findings clearly to both technical and non-technical audiences.
• Proven success working in fast-paced, cross-functional environments to drive high-impact outcomes.

This is a unique opportunity to join a dynamic, data-driven organization and make a significant impact on the success of its GTM strategy. If you’re passionate about using data to drive innovation and thrive in a high-growth environment, this role is for you!

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AI Software Engineer

Remote (US – ET/CT Time Zone)
$120K-$160K + Benefits

I’m partnering with a global leader in digital learning technology that’s transforming how millions of students and educators experience personalized, AI-powered learning. Following major investment in generative AI, the company is scaling its AI Platform Engineering team to build the next generation of adaptive learning tools.

This is a hands-on engineering role focused on building production-grade generative AI applications that power multiple products across the business.

The Role:

You’ll design and build scalable, full-stack systems that integrate large language models and AI capabilities into digital learning platforms. Working closely with data scientists, product managers, and engineers, you’ll help take GenAI prototypes from experimentation to production-driving forward real-world AI impact.

Key Responsibilities

• Develop and maintain AI-powered applications and platform services that are reliable, scalable, and secure
• Build and optimize LLM-based and RAG-powered solutions using frameworks such as LangChain or LangGraph
• Collaborate with Data Science teams to productionize models and streamline deployment pipelines
• Lead and contribute to technical design, architecture, and CI/CD improvements
• Ensure applications meet accessibility (WCAG 2.2 AA), performance, and security standards
• Stay current on the latest advancements in GenAI and advocate for best practices across the team

About You

• 5+ years of professional software engineering experience
• Strong full-stack skills across:
• Backend: Python, Node.js, or Go
• Frontend: Angular or React
• Databases: MySQL/PostgreSQL + NoSQL (e.g., DynamoDB)
• Cloud/Infra: AWS or Azure, Terraform, CI/CD tools
• Hands-on experience building AI/GenAI-enabled applications (Azure OpenAI, Amazon Bedrock, etc.)
• Practical understanding of RAG techniques, vector databases, and AI orchestration tools
• Strong system design, performance optimization, and collaboration skills
• Passionate about building impactful technology and staying ahead in the AI space

To Apply for this Job Click Here

To Apply for this Job Click Here

Staff Analytics Engineer

Location: Remote
Salary: $200-250k

Are you a data expert ready to drive transformative analytics at a cutting-edge cloud platform company? This fast-growing Series C innovator is revolutionizing how teams build, preview, and deploy high-performance digital applications.

About the Role

The Staff Analytics Engineer will lead the design and implementation of robust data models and pipelines, enabling business units to uncover insights and make data-driven decisions. This role is a unique chance to collaborate with engineering, product, and business teams, building scalable analytics systems that power operational efficiency and growth.

Key Responsibilities

• Design and maintain scalable data models and pipelines to serve as a single source of truth across the enterprise.
• Develop tools to enhance data accessibility, auditing, and validation, ensuring consistent, trustworthy datasets.
• Partner with cross-functional teams to uncover actionable insights and support decision-making.
• Build self-service analytics tools and dashboards for key stakeholders, streamlining workflows.
• Collaborate on advancing the company’s data platform using cutting-edge tools like dbt, Snowflake, and Superset.
• Lead initiatives to improve data quality, governance, and discoverability, ensuring alignment with business goals.

About You

• 8+ years of experience in analytics engineering or a similar role in a modern tech company.
• Advanced proficiency in SQL, with experience working on complex datasets.
• Expertise in data platforms like Snowflake or BigQuery and transformation tools like dbt.
• Familiarity with programming languages such as Python, Java, or Go.
• Experience with BI tools like Hashboard or Superset, and a strong grasp of schema design and dimensional modeling.
• Strong communication skills and the ability to collaborate in a fast-paced environment.

Be part of a forward-thinking team where data is at the core of every decision. If you’re passionate about transforming data into meaningful insights, this role offers the chance to work on impactful projects, collaborate with top talent, and make a lasting difference.

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To Apply for this Job Click Here

Staff Marketing Analyst

Location: New York (Hybrid)

Salary: $200,000-$250,000 Base + Bonus + Equity

Join a high-growth SaaS innovator backed by top-tier investors as they scale their Marketing Analytics capabilities to power the next phase of growth. This Staff Marketing Analyst position sits at the intersection of data, marketing, and business strategy-delivering the insights that drive pipeline, accelerate conversion, and optimize customer acquisition across all go-to-market motions.

THE ROLE

As a Staff Marketing Analyst, you’ll own the strategy, architecture, and execution of marketing analytics. You’ll partner closely with Growth, Demand Gen, Digital, and Product Marketing teams to define KPIs, analyze performance, and bring visibility to what’s working and what’s not. Your work will influence campaign spend, GTM roadmap, and executive decision-making.

Key Responsibilities:

• Define and evolve core marketing metrics across the funnel: acquisition, pipeline velocity, ROI, CAC, and attribution.
• Deliver clear, actionable insights through in-depth analysis of cross-channel campaigns (digital, paid, content, lifecycle).
• Build scalable dashboards and automated reporting to support real-time visibility for GTM leaders.
• Partner with RevOps and Sales Analytics to align marketing efforts with revenue impact and customer segmentation.
• Identify optimization opportunities through experimentation frameworks, A/B testing, and customer behavior modeling.
• Develop and maintain clean, well-modeled marketing data sets for long-term scalability and growth analysis.

ABOUT YOU

Required:

• 7+ years of experience in analytics, with a strong track record in Marketing or GTM Analytics at a SaaS or high-growth tech company.
• Advanced SQL skills and deep experience with BI tools like Looker, Mode, or Hashboard. Experience with Python or R a plus.
• Strong understanding of modern SaaS marketing channels and KPIs (e.g. MQL, SQL, pipeline contribution, CAC, LTV).
• Strategic thinker with the ability to translate complex data into simple insights and present them to cross-functional stakeholders.
• Comfortable operating independently in a fast-paced, collaborative environment where priorities evolve quickly.

WHAT’S ON OFFER

• High-impact, high-visibility role with ownership across the full marketing analytics stack.
• Competitive compensation and equity at a top-performing AI-driven SaaS brand.
• Opportunity to shape analytics foundations and influence GTM strategy at scale.
• Collaborative culture, modern tech stack, and hybrid flexibility in NYC.

To Apply for this Job Click Here

To Apply for this Job Click Here

Staff Data Scientist (Product)

Location: Remote

Salary: $190-220k

We’re partnering with a fast-growing SaaS company to find a Staff Data Scientist for a senior, high-visibility role embedded in their product organization. This is for someone who combines deep statistical expertise with the ability to influence how an entire company makes decisions – not just someone who runs experiments, but someone who builds the culture and infrastructure around them.

What You’ll Be Doing

• Owning and advancing the company’s experimentation roadmap, focused on high-leverage product questions around customer workflows, churn risk, and long-term value
• Designing and analyzing complex A/B tests, multivariate experiments, and Bayesian methods to measure the real impact of product 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 meaningful 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 Product Data, acting as a strategic thought partner across Product, Engineering, Finance, Design, and Product Marketing. The company is at an inflection point in how it uses data to make product decisions, 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 developing

Nice to have:

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

To Apply for this Job Click Here

To Apply for this Job Click Here

Senior Data Platform Engineer

Location: Los Angeles, CA

Salary: $160-200k base

We’re partnering with a fast-scaling, mission-driven advanced technology company building complex software and hardware systems deployed in real-world environments. Their platform processes and operationalizes high-volume data to power critical decision-making across the organization.

They are hiring a Senior Data Platform Engineer to design and scale the core data infrastructure that supports company-wide operations.

The Role

As a Senior Engineer on the Data Platform team, you will:

• Design and build scalable data pipelines and transformation frameworks
• Own ingestion and egress systems that unify multiple operational data sources
• Develop reliable, secure data models that power internal data products and applications
• Partner with engineering, product, and operations to translate business needs into production-grade systems
• Advocate for best practices across testing, CI/CD, data modeling, and security
• Debug and optimize complex transformation pipelines in production environments

What They’re Looking For

• 5+ years of experience in data engineering or backend engineering
• Strong programming skills in Python or similar languages
• Experience with Spark, PySpark, SQL, and dbt
• Familiarity with large-scale data platforms and cloud environments (AWS, Azure, or GCP)
• Experience with containerization and modern deployment practices
• Ability to operate autonomously in fast-moving environments
• Strong ownership mindset and attention to security best practices
• Must be a U.S. Person due to export-controlled information requirements

This is a high-impact role focused on building durable data systems that directly support operational execution at scale.

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 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

To Apply for this Job Click Here

To Apply for this Job Click Here

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

To Apply for this Job Click Here

To Apply for this Job Click Here

Staff Machine Learning Scientist

Location: SF Bay Area – Hybrid (3 days/week onsite)

Salary: $200-260k base + Equity

A leading commerce marketplace with 130M+ users and billions of daily events is hiring a Staff Machine Learning Scientist to drive innovation across personalization, feed ranking, computer vision, and GenAI. You’ll work on high-impact ML solutions that directly shape user experience and business outcomes at massive scale.

What You’ll Do

• Lead full-lifecycle ML projects from idea to production across core areas like personalization, trust & safety, marketing optimization, and user engagement.
• Own the ML development process-from data exploration and feature engineering to model training, deployment, and post-launch optimization.
• Collaborate cross-functionally with ML engineers, PMs, and business stakeholders to identify and prioritize high-leverage initiatives.
• Experiment with emerging AI techniques, including GenAI, computer vision, and LLMs, to push the boundaries of what’s possible on the platform.
• Build scalable, production-ready ML systems that enhance key metrics like retention, engagement, and conversion.

What You Bring

• 7-10 years of experience building, deploying, and maintaining ML models at scale.
• Deep expertise in Python, SQL, Spark (PySpark or Scala) and frameworks like PyTorch or TensorFlow.
• Proven track record in consumer tech or large-scale marketplaces companies.
• Hands-on experience with CNNs, Transformers, Vision Transformers, and personalization algorithms.
• Background in user behavior modeling, search relevance, or real-time data systems.
• Strong foundation in experimentation (A/B testing), statistics, and applied ML.
• Exceptional communication skills and the ability to translate technical insights into business value.

• Experience with LLMs, RAG (Retrieval-Augmented Generation), or PEFT (Parameter-Efficient Fine-Tuning) techniques.

To Apply for this Job Click Here

To Apply for this Job Click Here

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

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

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