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Staff Data Engineer

San Francisco, CA

$240K-$300K 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

• 8+ 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
• Deep experience with Kafka and streaming data systems, with strong working knowledge of ClickHouse, Iceberg, or similar technologies
• Experience with ingestion tools such as Fivetran, Airbyte, or Polytomic
• Cloud-native architecture expertise across AWS, GCP, or Azure
• Experience designing and scaling data systems to support petabyte-level workloads
• Track record of building data infrastructure that meets compliance and governance requirements, including SOX or equivalent
• Strong communication and collaboration skills, with the ability to operate as a senior technical voice across engineering and business stakeholders

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Head of Analytics & Data Science

Location: USA (Remote/Hybrid)

Salary: $230,000 – $260,000 base + performance bonus + extensive benefits

Harnham is partnering with one of the world’s most downloaded wellness apps, backed by a major public healthcare company, to hire a Head of Data Analytics. With 85M+ downloads and a global user base, this is a chance to lead analytics and data science for a brand millions already use, with startup-level ownership and the resources of a public company.

This is a player-coach role at the center of product, growth, and data science. You’ll be hands-on with metrics, experiments, and analysis, while also setting the data agenda alongside product, growth, and executive leadership.

What You’ll Be Doing

• Own core growth and subscription metrics (installs, trials, ROAS, CAC, LTV, churn) and lead attribution strategy across AppsFlyer, SKAN, and SSOT deduplication
• Run the experimentation program, helping PMs and UA design tests and build statistical rigor across the org
• Own product analytics strategy: event taxonomy, Mixpanel governance, and turning data into funnel and retention insight for PMs
• Manage and grow a team of data scientists, setting the analytics roadmap and priorities
• Act as the go-to data partner for UA, Growth PM, and Head of Product on key business decisions
• Build AI-powered self-service analytics tools so teams can answer their own questions
• Partner with data engineering to keep the underlying pipeline reliable and trustworthy

What You’ll Bring

• 7+ years in data/analytics roles, including 2+ years managing a team
• Strong grasp of subscription and mobile metrics: LTV, trial conversion, cohort analysis
• Experience with mobile UA attribution (MMP, SKAN, multi-touch) and cross-platform reporting
• A track record designing and running experimentation programs
• Product analytics experience: event instrumentation and Mixpanel/Amplitude governance
• Comfortable with dbt/SQL to review models and unblock your team when needed
• Sharp business partnering skills: plain-language communication and confidence to push back
• Hands-on experience building with AI/LLM tools, not just using them

Bonus points: background in consumer subscription apps (health, wellness, entertainment, or productivity); experience building internal AI-powered tools (Claude/OpenAI APIs, LangChain, agent tooling); deep attribution and data modeling expertise.

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Product Marketing Manager – Mobile Gaming

Location: Miami, FL (Hybrid)

Salary: $140,000-170,000

Job type: Full-time, Permanent

We’re partnering with a leading mobile game studio in Miami, part of a major international gaming group, to hire a Product Marketing Manager for its flagship title.

This is a rare opportunity to own the full player journey for one of the most recognizable games in its genre, from first ad impression to long-term retention, and turn new content launches into viral cultural moments.

Why This Role?

You’ll be the bridge between the development team and millions of players, owning full-funnel marketing strategy for a chart-topping mobile game. You’ll shape how new features and content packs go to market, drive aggressive organic growth, and lead expansion into new international markets, with real budget ownership and cross-functional influence from day one.

What You’ll Be Doing

• Define target audiences using player data, user research, and community insight, and dig into what’s driving unexpected player trends
• Shape product positioning and brand narratives that turn content updates into must-play moments, backed by competitive analysis and market research
• Design and execute full-funnel go-to-market (GTM) plans that integrate product features with user acquisition (UA), owning budgets and success metrics along the way
• Lead user acquisition and retention campaigns across paid, organic, PR, social, and non-traditional channels, including live events, influencer partnerships, and referral programs
• Build co-marketing and collaboration strategies with influencers, IPs, and consumer brands, coordinating cross-functional teams across product, paid UA, data science, and creative
• Partner with ASO and creative teams to optimize the App Store funnel, listings, and featured placements
• Own CRM and lifecycle marketing strategy to keep every player segment engaged
• Measure marketing impact through incrementality analysis, brand lift studies, and marketing mix modeling (MMM), using the data to optimize spend

What You’ll Bring

• 5+ years of product marketing experience in gaming or entertainment (mobile gaming strongly preferred)
• Bachelor’s degree or MBA in Marketing or a related field
• A proven track record of product marketing strategies and activations that delivered measurable growth
• Fluency in mobile gaming metrics (LTV, retention curves, ROAS, CPI) and the ability to turn analytics into action
• Strong cross-functional leadership: you can align developers, data scientists, and creatives around one goal
• A genuine passion for games and a sharp read on industry trends and the psychology of player engagement

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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

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Staff Product Analyst

Location: San Francisco (Remote Eligible)

Salary: $200K-$240K base + Equity

We’re hiring a Staff Product Analyst for a hyper-growth, Series E AI company valued at $3B+. This is an opportunity to play a key role in shaping product strategy and growth by leveraging data to drive decisions, optimize user experiences, and unlock new opportunities.

What You’ll Do:

• Shape product strategy with data-driven insights – Define key metrics, track user behavior, and identify trends that impact engagement and retention.
• Deep-dive into user journeys – Uncover friction points and growth levers to enhance adoption, conversion, and retention.
• Optimize experimentation and A/B testing – Design and analyze tests to improve product features, pricing, and personalization strategies.
• Develop self-service analytics tools – Build dashboards and automated reporting to empower teams with real-time data.
• Partner with Product, Engineering & Leadership – Translate complex data into clear, actionable recommendations to improve product performance and business outcomes.

What We’re Looking For:

• 7+ years of experience in Product Analytics, preferably within high-growth tech companies.
• Expert SQL skills and experience working with large-scale product datasets.
• Proficiency in Python or R, with a strong foundation in statistical analysis and experimentation.
• Hands-on experience with A/B testing methodologies and user segmentation.
• Experience with ELT data modeling and BI tools like Looker, Omni, or Hashboard.
• Strong executive communication skills, with the ability to influence product decisions through data.
• Thrives in a fast-paced, high-impact environment, with a passion for uncovering insights that drive product growth.

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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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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.

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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.

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Data Engineer

Location: Redwood City, CA (Hybrid – Tuesday, Wednesday, Thursday)

Salary: $120-150k base + Equity

Harnham has partnered with a Series B PropTech startup on a mission to make quality housing more affordable and accessible. Fresh off a new funding round and backed by leading investors, the company is scaling operations and entering new markets. With that growth, their data demands have outpaced the current team, and they now need a dedicated Data Engineer.

The Role

This hire will own the company’s data from end to end: understanding the source systems, building and maintaining the core datasets the business trusts, and turning raw operational data into clear, decision-ready outputs. They will work closely with Finance, Operations, and leadership to keep data accessible and useful as the company grows.

Responsibilities:

• Own the data pipelines: take responsibility for a portfolio of existing production ETL pipelines, handling daily maintenance, monitoring, and reliability so stakeholders can trust the data
• Design and build new pipelines: architect scalable ETL/ELT workflows that ingest data from new sources and grow with increasing data volume and complexity
• Build and own core datasets: design and maintain the sources of truth for business reporting and decision-making
• Master the source systems: ERP, CRM, project management, and finance platforms (NetSuite, Salesforce, and similar operational tools), understanding how data maps to real business processes
• Democratize data access: deliver well-documented, self-service-ready data products for Finance, Ops, and go-to-market teams
• Expand analytical coverage: identify opportunities for new tables, metrics, and derived datasets that unlock insight
• Set the standards: evolve data modeling, testing, documentation, and ownership practices from the ground up

The Ideal Candidate

• 2-4 years as a Data Engineer, building core datasets and supporting business teams
• Proven ETL and data pipeline ownership: experience building, maintaining, and monitoring production pipelines end to end, not just contributing to someone else’s
• Advanced SQL and strong data modeling skills, with experience designing analytical models that support real reporting and analytics use cases
• Hands-on experience shipping scalable cloud data solutions (AWS, Databricks, dbt) across methodologies like dimensional modeling, data marts, or medallion architecture
• Comfort tracing data through source systems and multiple layers of transformation
• A fast learner’s mindset: thrives in environments where priorities evolve and there’s always a new system or domain to pick up

Bonus points for:

• Integrating financial/ERP/CRM/payment systems (NetSuite, Salesforce, or similar)
• Aggregating from diverse sources, including APIs, geospatial imagery, unstructured web data, and public government records
• Exposure to feature engineering, forecasting, or AI-adjacent analytics
• Curiosity about AI tooling. No expertise needed, just a willingness to work smarter with it

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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 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

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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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