
Data Engineer
6 days ago
**Key Responsibilities**:
- Lead design and implementation of robust ETL pipelines using Informatica PowerCenter and Oracle Data Integrator.
- Develop and optimize data ingestion processes for large-scale data platforms including Hadoop and cloud-based solutions (AWS S3, AWS Glue, Azure Data Factory).
- Collaborate with business stakeholders to gather requirements and translate them into scalable data processing workflows.
- Manage and mentor ETL teams through development, code review, testing, deployment, and post-implementation support.
- Design and maintain Hive external tables and execute Sqoop jobs to move data between RDBMS and Hadoop HDFS.
- Perform data quality validation, root-cause analysis, and implement performance tuning techniques to resolve bottlenecks.
- Create ODI packages and workflows for complex data transformations and ensure high availability of critical data services.
- Drive migration strategies, support production rollouts, and manage issue tracking with JIRA and HPQC.
- Utilize scheduling tools such as Control-M and Tidal for job orchestration and workflow management.
- Contribute to Agile/SCRUM ceremonies and ensure timely delivery of development sprints
**Technical Skills**:
- ETL Tools: Informatica PowerCenter (8.6 - 10.1), Oracle Data Integrator (ODI 12.2.3.1), Pentaho
- Big Data Technologies: Hadoop, HDFS, Hive, Sqoop, PySpark, Scala
- Cloud Platforms: AWS (S3, Glue), Azure (Data Factory)
- Databases: Oracle, Teradata, MySQL, Exasol
- MDM Tools: Informatica MDM
- Reporting Tools: Tableau
- Schedulers: Control-M, Tidal
- Version Control / Issue Tracking: JIRA, Perforce
- Operating Systems: UNIX, Windows
- Methodologies
- : Agile, SCRUM
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