Senior Data Engineer

16 hours ago

India Donyati Full time

Senior Data Engineer Job Title: Senior Data Engineer Location: Remote/ Willing to Travel Job Type: Full-time Experience Level: 8+ years About the Role: We are seeking a highly skilled Senior Data Engineer to join our team in building a modern data platform on AWS. You will play a key role in transitioning from legacy systems to a scalable, cloud-native architecture using technologies like Apache Iceberg, AWS Glue, Redshift, and Atlan for governance. This role requires hands-on experience across both legacy (e.g., Siebel, Talend, Informatica) and modern data stacks. Responsibilities: - Design, develop, and optimize data pipelines and ETL/ELT workflows on AWS. - Migrate legacy data solutions (Siebel, Talend, Informatica) to modern AWS-native services. - Implement and manage a data lake architecture using Apache Iceberg and AWS Glue. - Work with Redshift for data warehousing solutions including performance tuning and modeling. - Apply data quality and observability practices using Soda or similar tools. - Ensure data governance and metadata management using Atlan (or other tools like Collibra, Alation). - Collaborate with data architects, analysts, and business stakeholders to deliver robust data solutions. - Build scalable, secure, and high-performing data platforms supporting both batch and real-time use cases. - Participate in defining and enforcing data engineering best practices. Required Qualifications: - 8+ years of experience in data engineering and data pipeline development. - Strong expertise with AWS services, especially Redshift, Glue, S3, and Athena. - Proven experience with Apache Iceberg or similar open table formats (like Delta Lake or Hudi). - Experience with legacy tools like Siebel, Talend, and Informatica. - Knowledge of data governance tools like Atlan, Collibra, or Alation. - Experience implementing data quality checks using Soda or equivalent. - Strong SQL and Python skills; familiarity with Spark is a plus. - Solid understanding of data modeling, data warehousing, and big data architectures. - Strong problem-solving skills and the ability to work in an Agile environment. - Expertise in Databricks, including designing and optimizing workflows within the Databricks environment.

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