Data Engineer

Expert SQL proficiency (advanced query optimization, performance tuning, database internals, analytical queries) Strong database fundamentals (join types, index vs. sequential scan tradeoffs, query optimization, materialized views, incremental computation, transaction isolation, concurrency control) Proficient Python (scripts for data processing/transformation, data libraries, API integrations, automation, code quality/testing) Strong Change Data Capture (CDC) experience (tools like Debezium, AWS DMS, log-based replication, schema evolution, semantics, idempotency, backfilling) 3+ years of dbt experience (building and scaling dbt projects, semantic layer/dimensional modeling, incremental models/materialization, testing, documentation, CI/CD, package management) 3+ years of Snowflake experience (S3 integration/external stages, Snowpipe, warehouse sizing/cost optimization, serverless features/task orchestration, data sharing, performance monitoring, governance, micro-partitions/clustering) Foundational understanding of event time vs. processing time, watermarks/late data handling, backfilling strategies, stream-to-stream joins, and windowing operations Required BI tool experience (building reports, dashboards, visualizations in platforms like Looker, Tableau, Power BI, Metabase; translating business needs, optimizing data models, stakeholder collaboration) 3+ years of production data engineering experience 3+ years working with dbt or similar transformation frameworks 3+ years hands-on experience with Snowflake Experience building CDC pipelines and handling real-time data ingestion Demonstrated ability to build reports and dashboards in BI tools Track record of building and maintaining data pipelines at scale Experience with data quality validation and reconciliation Track record of optimizing data platform performance and costs

Design, develop, and maintain scalable data pipelines and transformations Build and optimize complex SQL queries and data models Implement and manage real-time and batch data ingestion workflows using CDC Orchestrate end-to-end data pipelines with monitoring and alerting Build reports and dashboards in BI tools to support business analytics Collaborate with analytics and engineering teams to deliver reliable data solutions Ensure data quality, consistency, and reconciliation across the pipeline Monitor and optimize data platform performance and costs Ensure data quality, reliability, and governance standards