Hands-on Technical Lead to spearhead a Business As Usual (BAU) Data Engagement team owning the stability, reliability, and continuous improvement of Production data pipelines running on Google Cloud Platform.
Technical Lead will bridge the gap between technical execution and operational excellence managing the end-to-end data lifecycle from Data Lake to Dimensional/Fact tables, and ultimately to the Data warehouse
As a working lead the expectation is to mentor a Data Engineering team and dive into the code to implement SQL fixes, optimize DAGs and ensure bulletproof change management across the dev-to-prod lifecycle.
Lead and guide an offshore BAU production support team ensuring seamless overlap with US working hours.
Hands-On Production Support: Act as the ultimate point of escalation for troubleshooting, debugging, and resolving pipeline failures for data issues.
Pipeline Management & Optimization: Oversee the data flow architecture (Data Lake → Dims/Facts) and execute complex SQL fixes, DAG updates, data backfills,
and system validations. Rigorous Change
Control: Ensure all production deployments have comprehensive evidence, testing, and robust rollback plans before execution.
Continuous Improvement: Identify recurring issues in the data pipelines and implement proactive, automated solutions using Python and SQL to reduce technical debt and manual toil.
Required Skills & Experience Experience:
8+ years of dedicated Data Engineering experience with a proven track record of acting in a Team Lead or Technical Lead capacity.
GCP Data Stack: Deep hands-on expertise in Google BigQuery including advanced concepts like Slowly Changing Dimensions (SCD Type 1/2), partitioning, clustering, and cost optimization.
Orchestration: Extensive experience building and maintaining complex DAGs in Apache Airflow / Cloud Composer including proficiency with Jinja templating.
Programming: Robust proficiency in Python
📌 GCP Data Engineer (India)
🏢 Jobbycart technologies private
📍 India
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