Data Engineer with ETL Talend_ Remote

Job Description:

• Minimum 10 years of experience in Data Engineering with proven expertise in Talend as the primary ETL tool for enterprise data integration and migration.
• Extensive experience in data migration from legacy sources including MS Access, Excel, flat files, Kbase, and other proprietary systems into modern data warehouses and cloud platforms.
• Strong background in data ingestion strategies batch ingestion, near real-time, streaming pipelines with ability to design ingestion frameworks for structured, semi-structured, and unstructured data.
• Expertise in Data modeling (conceptual, logical, physical), dimensional modeling (star/snowflake), and database design principles tailored for healthcare, financial, or large-scale transactional systems.
• Skilled in building and optimizing data warehouses, data marts, and staging layers, ensuring efficient transformations and high query performance.
• Hands-on experience with Talend ingestion pipelines, job orchestration, and monitoring via Talend Administration Center (TAC) or external schedulers.
• Proficient in SQL, stored procedures, indexing, and query optimization with strong experience on SQL Server, Oracle, and other major RDBMS platforms.
• Deep understanding of ETL/ELT lifecycle design, including data mapping, lineage, transformation rules, reconciliation, and error-handling frameworks.
• Experience designing data ingestion frameworks with scalability in mind, supporting both on-premise and cloud data platforms (Azure, AWS, Google Cloud Platform, Snowflake).
• Strong knowledge of data quality frameworks, profiling, validation checks, and reconciliation to maintain trusted datasets for business analytics.
• Ability to design secure ingestion pipelines with robust error recovery, logging, auditing, and monitoring mechanisms.
• Exposure to cloud-native data ingestion services (Azure Data Factory, AWS Glue, Google Cloud Platform Dataflow) integrated with Talend for hybrid migration solutions.
• Familiarity with metadata management, master data management (MDM, and governance standards to ensure accuracy, compliance, and audit readiness.
• Strong collaboration with data architects and solution designers to define ingestion patterns, integration approaches, and scalable architecture blueprints.
• Demonstrated leadership in data modernization projects, mentoring junior engineers, and driving ingestion/migration initiatives with measurable outcomes such as reduced processing times, improved data quality, and successful legacy decommissioning.

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