Senior Oracle Data Integrator Consultant

EY; Dadri; On-site; INR 2,000,000 - 3,600,000; Full time

Job summary

EY Consulting is seeking a Senior Data Engineer (AWS & ODI) in India to design, build, and modernize enterprise data platforms. The role focuses on scalable ETL/ELT pipelines, cloud data processing, data quality, and reliable analytics-ready datasets.

You will work with ODI, AWS services (S3, Glue, Redshift), and PySpark to deliver robust data solutions. As part of a cross-functional team, you will optimize performance, troubleshoot SQL/PL-SQL, and mentor junior engineers while adhering to

Qualifications

• Hands-on ODI with mappings, packages, scenarios, load plans.
• Experience with AWS data engineering: S3, Glue, Redshift.
• SQL/PL-SQL, data warehousing and ETL/ELT concepts.

Responsibilities

• Design, develop, test, and support ODI ETL/ELT solutions.
• Build and optimize AWS data pipelines with S3, Glue, Redshift.
• Develop PL/SQL procedures, functions, packages, triggers.
• Analyze and troubleshoot SQL/PL-SQL code and data issues.
• Orchestrate workflows with Apache Airflow, monitor jobs.
• Contribute to data lake/lakehouse solutions including Iceberg.
• Mentor junior team members and improve delivery practices.

Skills

ODI

AWS

SQL

PL/SQL

PySpark

Airflow

Iceberg

Data warehousing

ETL/ELT

Data quality

Tools

S3

AWS Glue

Amazon Redshift

Job description

Job Summary

EY-Consulting - Data Engineer (AWS & ODI) | Senior

We are looking for an experienced Data Engineer with strong Oracle Data Integrator (ODI) and AWS data engineering experience to build, enhance, and modernize enterprise data platforms. The role focuses on scalable ETL/ELT pipelines, cloud-based data processing, data quality, and reliable delivery of analytics-ready datasets.

Your Key Responsibilities

• Design, develop, test, and support ETL/ELT solutions using Oracle Data Integrator (ODI).
• Build and maintain AWS data pipelines using services such as Amazon S3, AWS Glue, Amazon Redshift, and related cloud services.
• Develop and optimize data transformation logic using SQL, PL/SQL, and PySpark.
• Create and maintain PL/SQL procedures, functions, packages, triggers, and scripts to support data integration and processing requirements.
• Analyze and troubleshoot SQL and PL/SQL code, resolve data issues, and support basic performance improvements.
• Support data ingestion, integration, validation, reconciliation, and production deployment activities.
• Orchestrate and monitor workflows using Apache Airflow or equivalent scheduling tools.
• Contribute to data lake and lakehouse solutions, including Apache Iceberg-based implementations where applicable.
• Investigate pipeline failures and improve performance, stability, and operational reliability.
• Collaborate with business, analytics, architecture, and engineering teams to translate requirements into scalable data solutions.
• Follow engineering standards for documentation, code reviews, version control, testing, and release management.
• Mentor junior team members and contribute to continuous improvement of delivery practices.

Skills and Attributes for Success

• Strong hands-on experience in Oracle Data Integrator (ODI), including mappings, packages, scenarios, load plans, and knowledge modules.
• Hands-on AWS data engineering experience with S3, AWS Glue, and Amazon Redshift.
• Strong SQL skills and sound understanding of data warehousing, dimensional modelling, and ETL/ELT concepts.
• Working experience in PL/SQL development, including procedures, functions, packages, triggers, cursors, exception handling, and query troubleshooting.
• Experience with PySpark or distributed data processing frameworks.
• Experience with workflow orchestration using Apache Airflow or similar tools.
• Understanding of data quality, logging, monitoring, error handling, and performance optimization.
• Ability to work independently, communicate clearly, and collaborate across distributed teams.