Roles and Responsibilities

• Design and develop scalable ETL processes to extract, transform, and load data from a variety of source systems into enterprise data warehouses or data lakes.
• Analyze source systems, define data mappings, and produce detailed technical specifications for ETL workflows.
• Implement robust data quality checks, validation rules, and error handling mechanisms in all ETL pipelines.
• Optimize ETL jobs for performance, efficiency, scalability, and fault tolerance.
• Collaborate with data architects, analysts, and business stakeholders to translate data requirements into technical solutions.
• Schedule, monitor, and troubleshoot ETL workflows to ensure timely and accurate data delivery.
• Maintain comprehensive documentation for ETL designs, data flows, dependencies, and support processes.
• Provide ongoing metrics, logging, and status reporting on ETL and pipeline health.
• Participate actively in Agile ceremonies such as sprint planning, daily stand-ups, and retrospectives.
• Mentor junior ETL developers and contribute to knowledge sharing, standardization, and automation best practices.

Required Skills and Qualifications

• 8+ years of hands-on ETL development and data integration experience.
• Proficient in ETL tools such as Informatica, Talend, SSIS, IBM DataStage, or similar.
• Strong SQL programming skills and experience with relational and non-relational databases.
• Solid understanding of data warehousing concepts, data modeling, and star/snowflake schemas.
• Experience working with cloud data platforms (e.g., AWS, Azure, Google Cloud, Snowflake, Redshift, BigQuery).
• Expertise in performance tuning, pipeline automation, and scheduling tools.
• Familiarity with Agile methodologies and DevOps practices in data engineering.
• Excellent problem-solving, communication, and documentation skills.

Preferred Qualifications

• Experience with Python, Spark, or other scripting frameworks for data transformation.
• Experience with data governance, metadata management, and lineage tracking.
• Exposure to CI/CD tools for ETL deployment and automation.

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