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Remote mid-level data engineer with common title and 3+ years, increasing applicant competition.
Core data engineering skills transferable across industries, though insurance/SaaS domain knowledge is beneficial.
Mandatory 3+ years plus specific GCP BigQuery/Dataflow skills enforce strict technical filters.
Build, optimize, and maintain ETL/ELT pipelines on Google Cloud (BigQuery, Dataflow, Cloud Composer) to support business intelligence and reporting.
Develop and tune complex SQL scripts and manage data warehouse schemas (Star/Snowflake) to ensure data integrity and performance across SaaS and insurance domains.
Collaborate with data teams to translate business metrics into technical data solutions and maintain high-quality code and documentation.
3+ years professional experience in data engineering with cloud-based data warehouses.
Expert proficiency in SQL, including advanced functions, query plan analysis, and DDL scripting.
Experience with Google Cloud ecosystem: BigQuery, Cloud Storage, IAM best practices.
Must have reliable workspace with 50 Mbps internet and ability to work 8 hours daily including 4 core US overlap hours (7:30pm–11:30pm IST).
Experienced individual contributor comfortable handling both new feature development and legacy pipeline troubleshooting in a SaaS insurance context.
Strong in optimizing data pipelines for performance and cost efficiency within GCP environment.
Capable of working remotely with US-based business teams and effectively communicating complex technical concepts in English.