Sr. Data Integration Engineer

WORK TO BE PERFORMED:Responsible for the design, development, implementation, and maintenance of new and existing Data Integration processes within the Strategic Data Platform and other data solutions implementations.Design, develop, maintain, enhance, and monitor Data Integration processes sourcing data from various structured and semi-structured data sources, transforming as per provided business rules or data mappings, and loading into target databases/services including DB2, AWS S3, and Apache Iceberg.Serve as a subject matter expert on multiple data integration projects, ensuring consistent design and efficient data processing.Play a leading role in Build, Test, and Implementation phases of assigned projects, with a diverse development team spread across multiple locations.Provide Level 2 and Level 3 technical support to mission-critical applications.Perform process improvement and re-engineering with an understanding of technical data problems and solutions as they relate to the current and future business environment.Analyze complex distributed production deployments and make recommendations to optimize performance.Design and develop innovative data solutions for demanding business situations.Develop and document Data Integration standards and procedures.Design reusable and portable Data Integration components.Transform flat delimited files into multiple formats, including Parquet, JSON, and Protobuf.Play a supporting role in Build, Test, and Implementation phases of assigned projects, with a diverse development team spread across multiple locations.Investigate production Data Integration issues and work to determine the root cause of problems.SKILL AND EXPERIENCE REQUIRED:5+ years in IT application development, with at least 5 years in Data Integration (ETL) Development, using tools such as Python, SQL and Unix Shell Scripting.Experienced practitioner with a proven track record of implementing mid-scale to large-scale Data Integration (ETL) solutions, performing data analysis and profiling, interacting with client management, and designing and architecting dynamic ETL solutions.Working knowledge for Data Types and Databases including Relational, Dimensional, Vertical and No SQL databases.Hands-on experience with data cleansing and data visualization and familiarity with Hadoop Ecosystem.Experience with platforms such Hive and Trino/Starburst.Strong conceptual knowledge of file formats such as JSON, Parquet and Protobuf.Capable of writing and optimizing SQL queries and stored procedures.Exposure to AWS Services including but not limited S3, PostgreSQL, Apache Iceberg and Kafka.Ideal candidate would have worked on a Scrum Team and familiar with using tools such as Jira and Git.Experience developing containerized Data Integration solutions using Kubernetes, Rancher, and CI/CD pipelines using Harness, Jenkins and Artifactory is a plus.Experience working with scheduling tools such as UC4, Control-M, or Autosys is a plus.