We are seeking a Data Engineer with strong experience in Oracle and Hadoop ecosystems to support large-scale data platforms within a financial services environment. This role focuses on building and optimizing high-performance data pipelines enabling data integration analytics and regulatory reporting across enterprise systems.
You will work in a highly regulated environment ensuring data solutions meet security governance and compliance standards.
Key Responsibilities
Design develop and maintain data pipelines using Oracle and Hadoop technologies
Build and optimize ETL/ELT processes for large-scale structured and unstructured data
Work with Hadoop ecosystem tools (Hive Spark HDFS Sqoop etc.)
Develop and optimize SQL/PLSQL queries stored procedures and performance tuning
Integrate data from multiple sources including transactional systems data warehouses and external feeds
Ensure data quality consistency and governance across platforms
Support data migration transformation and data modeling activities
Collaborate with business and analytics teams to deliver data-driven solutions
Ensure compliance with financial regulations audit requirements and data security standards
Required Skills
5 years of experience in data engineering / big data development
Strong expertise in Oracle (SQL PL/SQL performance tuning)
Hands-on experience with Hadoop ecosystem (Hive Spark HDFS MapReduce)
Experience building ETL/ELT pipelines and data integration workflows
Strong knowledge of data modeling and data warehousing concepts
Experience working in enterprise environments (financial services preferred)
Understanding of data governance security and compliance requirements
Preferred Qualifications
Experience with cloud platforms (AWS Azure GCP)
Experience with data streaming tools (Kafka Flink)
Familiarity with data lake / lakehouse architectures
Experience with Informatica Talend or similar ETL tools
Exposure to regulatory reporting and financial datasets
Interested Candidates
Please share your updated resume along with:
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Expected Salary
Data Engineer (Financial Services Enterprise Data Platform) Location: Onsite / Hybrid / Remote Employment Type: Full-Time (W2 Only) No Corp-to-Corp (C2C) About the Role We are seeking a Data Engineer with strong experience in Oracle and Hadoop ecosystems to support large-scale data platforms wit...
Data Engineer (Financial Services Enterprise Data Platform)
We are seeking a Data Engineer with strong experience in Oracle and Hadoop ecosystems to support large-scale data platforms within a financial services environment. This role focuses on building and optimizing high-performance data pipelines enabling data integration analytics and regulatory reporting across enterprise systems.
You will work in a highly regulated environment ensuring data solutions meet security governance and compliance standards.
Key Responsibilities
Design develop and maintain data pipelines using Oracle and Hadoop technologies
Build and optimize ETL/ELT processes for large-scale structured and unstructured data
Work with Hadoop ecosystem tools (Hive Spark HDFS Sqoop etc.)
Develop and optimize SQL/PLSQL queries stored procedures and performance tuning
Integrate data from multiple sources including transactional systems data warehouses and external feeds
Ensure data quality consistency and governance across platforms
Support data migration transformation and data modeling activities
Collaborate with business and analytics teams to deliver data-driven solutions
Ensure compliance with financial regulations audit requirements and data security standards
Required Skills
5 years of experience in data engineering / big data development
Strong expertise in Oracle (SQL PL/SQL performance tuning)
Hands-on experience with Hadoop ecosystem (Hive Spark HDFS MapReduce)
Experience building ETL/ELT pipelines and data integration workflows
Strong knowledge of data modeling and data warehousing concepts
Experience working in enterprise environments (financial services preferred)
Understanding of data governance security and compliance requirements
Preferred Qualifications
Experience with cloud platforms (AWS Azure GCP)
Experience with data streaming tools (Kafka Flink)
Familiarity with data lake / lakehouse architectures
Experience with Informatica Talend or similar ETL tools
Exposure to regulatory reporting and financial datasets