Skill: Senior Data Engineer
Strong hands-on with Hadoop ecosystem including -
- PySpark for scalable data processing.
- Hive and Impala for data warehousing and query based analysis.
- Linux/Unix - Scripting and operational troubleshooting.
- Solid understanding of distributed computing concepts, data partitioning and performance tuning on Hadoop.
- Proficient in developing and maintaining large-scale data pipelines and ETL workflows.
Good-to-Have Technical Skills:
- Exposure to ELK stack(Elasticsearch, Logstash, Kibana) for search-driven work sets.
- MongoDB for semi structure data storage and retrieval.
- Familiar with version control systems (Git), CI/CD pipelines and workflow orchestration tools like Apache Airflow.
Functional Knowledge:
- Prior experience or exposure to Banking domain.
- Understanding of Anti-Money Laundering (AML) processes, such as transaction monitoring, customer risk rating and case management workflows.
- Ability to interpret business rules related to AML.
- Responsible for designing, building and optimizing data pipelines that serve as the backbone for AML data analytics and reporting solutions.
- Closely work with data analysts, compliance teams and other technology partners to ensure data quality, lineage and timely availability.