Data Engineer (Google Cloud Platform)_ W2

Data Engineer (Google Cloud Platform) (Contract) Multiple Openings Type: Contract (6 months, likely extension, long term) Location: Remote (PST/EST overlap required) Technical Requirements Must-Have PySpark & Databricks: Strong hands-on experience building and maintaining production pipelines. Experience with Unity Catalog is a plus. Python Engineering: Primary development language with production-grade practices (typed, tested, modular code not notebook-only development). Google Cloud Platform Ecosystem: Proven experience with BigQuery, Dataproc, Airflow/Cloud Composer, Pub/Sub, and Cloud Storage (Parquet). Data Ingestion: Experience working with complex, multi-source datasets across varying schemas and formats (e.g., JSON, CSV, XML, custom feeds). Data Modeling: Strong understanding of staging and curated layer design, partitioning strategies, and schema evolution across distributed data sources. Experience Level: 4 7+ years of hands-on data engineering experience with a track record of building and maintaining production systems (not research-focused profiles). Nice to Have dbt: Experience working with dbt, ideally within a medallion/lakehouse architecture. Entity Resolution: Familiarity with record linkage techniques (fuzzy matching, phonetic similarity, Python-based frameworks). Domain Experience: Exposure to music, royalties, or media rights data is a plus.