Senior Software Engineer, Data Products
Senior engineer building performant user-facing data products from internal datasets using Python, Databricks, and Postgres while collaborating with platform teams.
Designs and runs massive-scale data pipelines for ingestion, normalization, enrichment, and delivery across 80M+ companies and 800M+ people. Manages data operations, BPO vendors, partnerships, monitoring, and cost optimization using Python, Dagster, and DuckDB.
Senior engineer building performant user-facing data products from internal datasets using Python, Databricks, and Postgres while collaborating with platform teams.
Lead and develop a team of analytics engineers to design, build, and maintain scalable data models, ELT pipelines, and BI solutions using modern data stack tools. Requires 7+ years data experience including 2+ years managing teams, deep expertise in SQL, Python, Snowflake, dbt, and dimensional modeling.
Owns the data warehouse, semantic layer, and ingestion pipelines using Snowflake, dbt, and Looker. Architects reliable data models, integrates new sources, enables AI workflows, and sets company-wide metrics standards. Requires 5+ years in analytics/data engineering with strong SQL, dbt, and Python.
Builds and scales ETL pipelines, designs data schemas, and owns data quality/governance for 10x growth. Requires 5+ years in data pipelines with SQL, Spark, Airflow, Python, and MPP databases like Snowflake/Redshift.
Develop distributed data systems including Apache Spark and Delta Lake to handle big data workloads efficiently. Requires 5+ years in Java/Scala/C++ and expertise in distributed systems.