DataStage Data Engineer

DataStage Data Engineer Design, develop, and support scalable IBM DataStage ETL solutions and enterprise data pipelines for mission-critical applications. Collaborate with business and technology teams to deliver high-quality, performant, and reliable data integration solutions aligned with enterprise architecture standards. The ideal candidate will have extensive experience working with multiple source and target systems including Oracle, DB2, Snowflake, flat files, cloud storage, structured, semi-structured, and unstructured data sources. The candidate should possess deep expertise in IBM DataStage, Snowflake, Unix Shell Scripting, PL/SQL. This role involves building scalable data pipelines, optimizing data movement processes, supporting data warehouse, data lake, and Lakehouse platforms, and enabling enterprise analytics and reporting solutions. Required Skills & Experience • Strong hands-on experience with IBM DataStage 11.7 or above including Parallel Jobs, Sequencers, Parameter Sets, Job • Monitoring, Administration, and Performance Tuning. • Advanced SQL and PL/SQL development skills with strong experience in Oracle and DB2 environments. • Design, develop, test, deploy, and support complex ETL/ELT solutions using DataStage and enterprise data pipelines. • Develop reusable ETL frameworks using IBM DataStage, parameterized jobs, metadata-driven solutions, and automated data processing workflows. • Analyze business and technical requirements and translate them into scalable ETL designs and data integration solutions. • Implement data extraction, transformation, validation, cleansing, reconciliation, and loading processes using DataStage. • Experience integrating data from Oracle, DB2, SQL Server, Snowflake, flat files, XML, JSON, Parquet, and cloud storage platforms using DataStage. • Strong experience with Snowflake including, Streams and Tasks, Dynamic Tables, Internal and External Stages, Secure Views, Data Sharing and Query Performance Optimization • Experience designing, developing cloud-native data pipelines, and migrating data from on-premises systems to Snowflake. • Strong Unix/Linux Shell Scripting skills for process automation, file handling, batch scheduling, operational support, and production troubleshooting. • Experience creating high-performance batch, incremental, and CDC-based data pipelines for large-volume data processing. • Strong understanding of ETL/ELT architecture, Data Warehousing, Dimensional Modeling, Data Lakes, and Data Lakehouse architectures. • Experience with performance tuning, root cause analysis, production support, and incident management. • Working knowledge of Git, CI/CD pipelines, Agile methodologies, and DevOps practices. • 8-10 years engineering experience EDUCATION REQUIREMENTS A Bachelor’s degree in computer engineering, computer science or other related discipline or the equivalent combination of education, training, or work experience.