Senior Data Engineer - Senior Manager

Prior experience in Data engineering, ETL, Data Ingestion and data warehousing and analytics with 8+ Years of experience. Design, develop, and support end‑to‑end data pipelines using cloud‑based platforms such as AWS, Redshift ,Databricks, and Snowflake. Build scalable data ingestion, transformation, and validation frameworks using Python, SQL, and Shell scripting. Develop and optimize data pipelines for performance, reliability, and data quality Strong background in data warehousing, ETL/data pipelines, and cloud‑based data warehouse solutions. Hands‑on experience delivering end‑to‑end data pipeline solutions encompassing architecture design, implementation, testing, deployment, monitoring, and operational support. Build and operate scalable batch and streaming pipelines using the Snowflake and/or Databricks tech stack, Spark , or Informatica ETL (where reused) to deliver analytics-ready datasets on AWS Cloud Platform. Design, implement, and optimize Iceberg -based tables, partitions, and metadata structures for consistent and performant analytical access Experience with MDM, Data Quality frameworks, and data management tools, including hands‑on implementation of automated data validation, quality rules, reconciliation checks, and lineage capture to ensure governed, reliable, and trusted analytical data across enterprise platforms. Work with Platform Engineering to standardize deployment via CI/CD, productionize jobs, and adopt platform guardrails and observability patterns Collaborate with architects and application teams to define data strategies and deliver logical/physical data models aligned to analytical workloads Optimize pipeline and query performance through appropriate database partitioning, archiving, and purging patterns Participate in on-call / major incident management, perform backfills where required, and support production stability for owned data products Ensure compliance with data security, governance, and SDLC standards Continuously identify opportunities to improve efficiency, automation, and platform capability Good hands-on to AWS Data storage products like AWS S3 and Amazon Redshift. Good Exposure to code versioning tool GIT, Harness, JFrog and CI/CD Process and project collaboration platform JIRA. Partner with product owners, analytics teams, and downstream consumers to translate business requirements into technical solutions Actively participate in architecture discussions, design reviews, and technical walkthroughs Follow Agile delivery practices, including sprint planning, estimation, and issue tracking using JIRA Excellent verbal and written communication and should be able to work with all the stakeholders.

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