Analytics Engineer
Analytics Engineer
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USD 140000 - 200000
1 Vacancy
Job Description
About Clay
Why is Clay the best place to work
Customers love the product (100K users and growing)
Were growing a lot (6x YoY last year and 10x YoY the two years before that)
Incredible culture (our customers keep applying to work here)
Well-resourced - We raised a $100M Series C in 2025 at a $3.1B valuation and are backed by world-class investors like Capital G (Google) Sequoia and Meritech
Read more about why people love working at Clay here and explore our wall of love to learn more about the product.
Analytics Engineer @ Clay
Were looking for an Analytics Engineer to bridge the gap between raw data infrastructure and high-impact business insights and data products. Youll take ownership of our data models pipelines and platform architecture to ensure our analytics and data science foundation is scalable durable and consumable. Your work will enable better decision-making across teams - from Product and Engineering to Marketing Finance and Ops.
Clays modern data stack includes Fivetran Segment Snowflake dbt Dagster Hex Sigma Eppo Census and youll play a key role in shaping how we use and evolve it to power strategic insight and operational excellence.
Impact Youll Have
Own data pipelines: Design build and maintain reliable ETL/ELT pipelines ensuring timely and accurate delivery of high-quality data across the organization
Build a scalable foundation: Find ways to leverage and improve our current data models by architecting resilient maintainable dbt models that serve as the trusted source of truth for analytics experimentation and data products
Collaborate cross-functionally: Work closely with data scientists engineers and business teams to understand use cases and proactively develop data assets that support their goals effectively and scalably
Drive architectural improvements: Identify opportunities to consolidate and improve our data platform proposing improvements that ensure long-term scalability and flexibility
Improve data quality discoverability and metric clarity: Design and implement robust systems for schema design data validation documentation and governance while defining and standardizing core business metrics and semantic definitions to ensure consistency across teams and tools
Support self-serve insights: Enable teams with intuitive trustworthy data products and tooling that allow less-technical users to explore data and develop solutions independently
Plan for the future: Help define the evolution of Clays data stack and architecture including how we consolidate transform and surface data and intelligence for emerging use cases
What Youll Bring
6 years of hands-on experience in analytics engineering data engineering or data management
Strong ownership mentality and proven ability to design for scalability durability and reusability
Expert in SQL Python AWS infrastructure and modern data tools (emphasis on dbt Dagster/Airflow)
A passion for pragmatic solutioning while staying current on modern data and AI tooling pushing the boundaries of GenerativeAIs role in Data Products and workflows
Excitement for iterative agile development processes and collaboration with diverse teams
Employment Type
Full-Time
