Analysis Skills, Apache Kafka, Big Data, Business Analysis, Cloud Computing, Communication Skills, Data Management, Data Quality, Data Warehousing Applications, Database Extract Transform and Load (ETL), Debugging Skills, IBM WebSphere DataStage, Identify Issues, Information Technology & Information Systems, Performance Tuning/Optimization, Problem Solving Skills, Production Support, Python Programming/Scripting Language, SQL (Structured Query Language), Scala Programming Language, Server Programming/Applications, Snowflake Schema, Software Engineering, Star Schema, Technical Support, Technical Writing, Unix Shell Programming
Work Location: Chicago, IL 60604 (Onsite)
Duration: 12 Months
Experience: 10+ Years
Job Summary
We are seeking an experienced Senior DataStage ETL Developer with strong expertise in IBM DataStage, Python, Spark, SQL, Scala, and Shell Scripting. The ideal candidate will have extensive experience in designing and developing ETL solutions, building enterprise data warehouse applications, and working with scheduling and messaging tools such as Control-M, Zena, and Kafka.
Required Skills
- 10+ years of IT experience with a strong focus on ETL and Data Warehousing.
- Hands-on experience with IBM DataStage development.
- Expertise in DataStage Designer, DataStage Director, and DataStage Operations Console.
- Strong experience designing and developing Server Jobs, Parallel Jobs, Job Sequencing, Parameter Sets, Containers, Environment Variables, and Parallel Routines.
- Strong knowledge of Data Warehousing, ETL, Star Schema, and Snowflake Schema concepts.
- Proficiency in Python, Spark, SQL, Scala, and Shell Scripting.
- Experience with Kafka for data integration and messaging.
- Experience using enterprise scheduling tools such as Control-M and Zena.
- Strong troubleshooting, debugging, and performance tuning skills.
Responsibilities
- Design, develop, and maintain ETL solutions using IBM DataStage.
- Build and optimize DataStage Server and Parallel jobs for enterprise data warehouse applications.
- Develop data integration workflows using Python, Spark, SQL, and Scala.
- Create and manage Job Sequences, Parameter Sets, Containers, and reusable ETL components.
- Perform data extraction, transformation, cleansing, validation, and loading activities.
- Integrate Kafka-based data pipelines with enterprise ETL solutions.
- Schedule, monitor, and manage ETL jobs using Control-M and Zena.
- Optimize ETL performance and troubleshoot production issues.
- Collaborate with business analysts, data architects, and development teams to deliver high-quality data solutions.
- Prepare technical documentation and support production deployments.
Preferred Skills
- Experience with Big Data technologies.
- Knowledge of cloud-based data platforms.
- Experience with performance tuning and ETL optimization.
- Strong analytical, communication, and problem-solving skills.
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