Job Title

Remote/Hybrid 4 - 7+ years Hands-On SQL About BuildingBlocks Regardless of whether accomplishing astounding customer work or aiding assemble our organization from the inside, our different gifted organization shares a solitary mission: to fabricate lovely encounters that decidedly affect individuals' lives and the organizations we serve. Our way of life is more reason than work, mixing the quest for certified human association with a fastidious way to deal with the things we make. All with an idealistic soul. We're an organization that is adequately youthful to be fun and defiant - yet intense and driven enough to immensely affect the business. Role Overview We're looking for a hands-on Data Engineer to own the data layer of customer go-lives "” ensuring migrations are validated, analytics pipelines are hardened, and business dashboards are powered by accurate, performant data. You'll be responsible for validating and signing off on end-to-end data migrations, building high-quality SQL models, and implementing automated data quality checks to catch issues early. This is a highl technical and impact-driven role focused on migration testing, SQL performance tuning, and data quality automation "” aligning with AWS and industry best practices. Key Responsibilities End-to-End Migration Validation: Design and execute functional and performance validation for data migrations "” including parity, nullability, PK/FK, duplication, and sampling checks "” with complete documentation and sign-off aligned to AWS migration testing guidelines. Advanced SQL Development: Write and optimize analytical SQL (CTEs, window functions, incremental loads). Use EXPLAIN plans to tune query performance and ensure indexes and statistics support BI workloads. Automated Data Quality Frameworks: Implement and maintain data validation frameworks using Great Expectations, Deequ, or similar tools. Automate validation and publish Data Docs to ensure transparency across teams. Modeling & Documentation (dbt): If using dbt, build models with tests, exposures, and documentation to ensure traceability between dashboards and upstream data sources. Orchestration & Reliability: Productionize data validation and transformation jobs within Airflow DAGs, ensuring welldefined SLAs, alerts, and reliable pipeline operations. (Optional) Cloud Data Engineering: Build incremental pipelines and optimize batch processing for Snowflake (Streams & Tasks) or PostgreSQL, ensuring performance and cost efficiency. Minimum Qualifications Experience: 4-7+ years as a Data Engineer or Analytics Engineer. SQL Expertise: Advanced proficiency in SQL and strong RDBMS fundamentals (PostgreSQL required), with proven experience in query tuning using EXPLAIN/analyze. Migration Validation: Hands-on experience designing and executing data migration validation (parity, integrity, and performance testing). Tooling Knowledge: Experience with one or more of the following "” dbt, Great Expectations or Deequ/PyDeequ, Airflow. Version Control: Comfortable with Git-based workflows and CI/CD integration. Nice to Have Experience with Snowflake (Streams, Tasks, cost optimization, and warehouse tuning). Exposure to BI tools such as Looker, Power BI, Tableau, or Metabase. Working knowledge of Python for lightweight data transformations and validation frameworks. Transcend your experience! Please select the services you are looking for #J-18808-Ljbffr