Senior Analytics Engineer

Salary

$150,000 - $200,000

Location

New York, NY

We are looking for an experienced data professional to join a renowned team that is transforming the future of renting, home ownership, and rewards. You will play a key role driving business growth by building the data foundation to unlock strategic & analytical insights, with an emphasis on structuring, modeling, testing and activating our data in dbt. You will take significant ownership of our BigQuery data warehouse, its performance and its role in connected applications. The ideal candidate has a proven track record developing data products and key stakeholder relationships. You will work directly with Bilt’s leadership as a key influencer driving growth and strategy at Bilt.

In this role, you will…

Be instrumental in growing Bilt’s analytics engineering function as the first hire dedicated exclusively to analytics engineering to support the business’ goals
Partner with the Data Analytics team to model data into usable and scalable formats to drive embedded and self-service analytics for internal and external stakeholders
Assist Data Analytics team with end-to-end development of models/tests/alerts/semantic models/metrics to be consumed by internal and external stakeholders
Identify and execute on opportunities for employing advanced analytics and building complex models to answer business problems such as sessionization of events data, marketing attribution, granular profit modeling, LTV and Churn
Identify and execute on cost and performance optimizations for existing models, including advanced incremental loading, indexing, and clustering strategies
Build strong relationships with engineering and business stakeholders and serve as a key centralized function to empower data-driven use cases
Accelerate our dbt instance from 1 to 100 and take ownership of core BigQuery data assets
Build technical integrations together with engineering stakeholders to scale and power Bilt’s overall data capabilities

In terms of qualifications, we’re seeking:

About you:
A data professional yearning to solve big-picture problems, learn new things, seek answers in data, who finds comfort in uncertainty
A natural communicator, who can think in terms of solutions instead of tools, and can explain sophisticated systems to technical and non-technical audiences with equal clarity
Engineering-minded with a strong bias towards action, delivering results quickly with iteration instead of waiting for perfection
Strong prioritization and organizational skills the ability to juggle many tasks at once in a fast-paced, entrepreneurial environment
Experience implementing advanced alerting and monitoring and building resilient systems and processes
A heart-first contributor who is able to deliver complex projects with multiple stakeholders
Experience:
6+ years of experience in analytics engineering or data engineering
A SQL wizard, who feels at home in a modern data warehouse (e.g. BigQuery, Snowflake) and experienced with Python, other programming languages such as Java a plus; statistics and/or machine learning experience also a plus
Experience with highly performant analytical databases (e.g. Clickhouse, DuckDB, AlloyDB) and/or caching layers (e.g. Redis) also a plus
Strong experience with dbt, comfortable owning / building out dbt projects, leveraging Jinja, YAML to enable analytics at scale, experience with dbt semantic layer or similar backend semantic modeling
Experience acting as lead for all things data warehouse, including permissions, data governance, scalability and reliability
Experience orchestrating large datasets and DAG dependencies; familiar with tools such as dbt Cloud, Airflow, Cloud Composer or similar tools
Experience applying best practices and frameworks such as DRY, incremental models, testing and alerting, and generating documentation
Partnering with Data Engineering to ingest and model new data sources, and manage database migrations
Experience with a variety of BI Tools (e.g. Sigma, Looker, Mode, Tableau etc.) and integrating dbt or equivalent semantic layer with these tools
Experience with reverse ETL solutions, syncing data assets to internal services and/or external platforms via a variety of SaaS / OSS tools (e.g. Census, Hightouch, Airbyte)

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