Senior Data Engineer
Spark Tek Inc
Job Description
Job Description
Location: San Jose, CA – Local Candidates Only
Job Type: Contract
Work Arrangement: Onsite – No Remote
- Lead end-to-end migration, transformation, and loading of high-volume, complex data into PostgreSQL.
- Design, build, and maintain scalable ETL/ELT pipelines processing millions of records.
- Map and reconcile complex legacy data structures across multiple business entities.
- Develop data validation and reconciliation frameworks to ensure data integrity and completeness.
- Optimize PostgreSQL performance through query tuning, indexing, partitioning, and batch/incremental loading.
- Troubleshoot data quality issues, schema mismatches, and pipeline failures.
- Document data mappings, transformation logic, data lineage, and migration runbooks.
- Collaborate with business and technical stakeholders on migration requirements and timelines.
- Establish monitoring, logging, and alerting for pipeline health and data quality.
- Mentor junior data engineers and contribute to engineering best practices.
- 7 years of experience in Data Engineering.
- Strong to expert-level Python skills.
- Deep hands-on experience with PostgreSQL and/or Oracle .
- Proven experience designing and managing ETL/ELT pipelines at scale .
- Experience with large-scale data migration projects involving millions of records.
- Strong experience with data mapping, transformation, validation, and reconciliation.
- Knowledge of data modeling, normalization, indexing, and partitioning.
- Experience with Git and CI/CD practices.
- Strong troubleshooting and problem-solving skills.
- Experience with Airflow, Dagster, or Prefect .
- Experience with AWS, GCP, or Azure .
- Exposure to NoSQL and cross-database migrations.
- Experience working in regulated or high-stakes data environments.
- Experience with Docker and Infrastructure-as-Code .
- Familiarity with Great Expectations, dbt tests , or similar data quality frameworks.
- Fully migrated and validated datasets in PostgreSQL with zero critical data loss or corruption.
- Documented, repeatable, and optimized ETL/ELT pipelines.
- Clear data lineage and audit trails for migration and validation activities.
Vacancy posted 15 days ago
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