7 - 10 years
30 - 45 Lacs
Posted:5 days ago|
Platform:
Hybrid
Full Time
Role & responsibilities * Design, Build, and Maintain ETL Pipelines: Develop robust, scalable, and efficient ETL workflows to ingest, transform, and load data into distributed data products within the Data Mesh architecture. * Data Transformation with dbt: Use dbt to build modular, reusable transformation workflows that align with the principles of Data Products. * Cloud Expertise: Leverage Google Cloud Platform (GCP) services such as BigQuery, Cloud Storage, Pub/Sub, and Dataflow to implement highly scalable data solutions. * Data Quality & Governance: Enforce strict data quality standards by implementing validation checks, anomaly detection mechanisms, and monitoring frameworks. * Performance Optimization: Continuously optimize ETL pipelines for speed, scalability, and cost efficiency. * Collaboration & Ownership: Work closely with data product owners, BI developers, and stakeholders to understand requirements and deliver on expectations. Take full ownership of your deliverables. * Documentation & Standards: Maintain detailed documentation of ETL workflows, enforce coding standards, and adhere to best practices in data engineering. * Troubleshooting & Issue Resolution: Proactively identify bottlenecks or issues in pipelines and resolve them quickly with minimal disruption.
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