Job Overview
We are seeking an experienced ETL & Big Data Developer with strong expertise in IBM DataStage and Hadoop ecosystem tools to join our dynamic data engineering team supporting a leading global banking client. This is an exciting opportunity to work on enterprise-scale batch data processing, data integration, and performance optimization in a hybrid cloud environment.
Key Responsibilities
- Design, develop, and maintain ETL pipelines using IBM DataStage.
- Work with big data platforms including Hadoop, Hive, HDFS, and Spark.
- Implement robust and scalable ETL workflows for large-scale batch processing.
- Optimize ETL jobs for performance, throughput, and error handling.
- Collaborate with data architects, analysts, and business teams to understand requirements and translate them into technical solutions.
- Ensure seamless data flow across upstream and downstream systems.
- Follow best practices for data governance, security, and compliance.
Required Skills & Experience
- 5–8 years of hands-on experience with IBM InfoSphere DataStage.
- Proficiency in Hadoop ecosystem tools like Hive, HDFS, Spark, and Oozie.
- Strong background in SQL, data warehousing, and data integration concepts.
- Familiarity with Unix/Linux shell scripting and job scheduling tools.
- Experience in performance tuning, job orchestration, and error handling mechanisms.
- Excellent problem-solving, debugging, and communication skills.
- Experience working in Agile/Scrum environments is a plus.
Nice to Have
- Exposure to cloud-based data platforms (AWS EMR, Azure HDInsight, or GCP Dataproc).
- Knowledge of Kafka, NoSQL databases, or real-time streaming technologies.
- Understanding of data governance frameworks and metadata management tools.
