Senior ETL Data Engineer

Job Description Position Summary: The Senior ETL Data Engineer supports cloud data operations by designing, developing, and deploying enterprise-level Extract, Transform, Load (ETL) data pipelines. This role curates, processes, and standardizes data across cloud and on-premise platforms while maintaining enterprise data governance, security, and quality standards. Key Responsibilities:

• Designs, develops, tests, and supports complex end-to-end data pipelines to ingest data from multiple sources into target tables and landing layers.
• Establishes and manages connectivity between cloud and on-premise environments using platforms such as Azure Data Lake Storage (ADLS) Gen2, Blob Storage, Azure Data Factory, Synapse, and Databricks.
• Automates, monitors, and optimizes existing data workflows to ensure system performance, data accuracy, security, and scalability.
• Consults with business units and technical teams to gather requirements, resolve system issues, and evaluate technical feasibility for system enhancements.
• Develops database queries, complex scripts, and reporting solutions to support enterprise business requirements.
• Implements system change evaluations, backup procedures, and rollback plans to ensure high data reliability.
• Serves as a technical subject matter expert (SME) on enterprise-wide data architecture and data governance best practices.

• Education: Bachelor’s degree in Information Technology, Computer Science, or a related field (or equivalent experience).
• ETL & Data Architecture: 10 to 15 years of experience developing end-to-end ETL processes, data architecture, data warehousing, and business intelligence solutions.
• Database & Querying Skills: 10 years of hands-on experience using SQL for relational databases (e.g., Oracle, SQL Server, Postgres, DB2).
• Data Formats: 10 years of experience working with diverse data formats, including relational, text (CSV, XML), and binary formats (Parquet, AVRO).
• Data Governance: 7 years of experience maintaining data governance, data security, and data consistency standards.
• Cloud Solutions: 5 years of hands-on experience with Microsoft Azure tools, including Azure Data Factory, Synapse Analytics, SQL DB, Data Lake Storage Gen2, and Blob Storage.
• Pipeline Integration: 5 years of experience utilizing integration tools such as Informatica PowerCenter, Apache NiFi, Apache Airflow, or FME.
• Core Competencies: Strong written and verbal communication skills with a proven ability to collaborate across multidisciplinary teams and support external partners., * Experience performing advanced data functions using Databricks.
• Familiarity with data visualization and reporting tools such as MicroStrategy, Tableau, or Esri ArcGIS.
• Experience with Python scripting for data pipeline automation.