EY - GDS Consulting - AI And DATA - Data Engineer-Senior

Ernst & Young Advisory Services Sdn Bhd; Chennai District; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

EY GDS Consulting - AI And DATA - Data Engineer-Senior is seeking a Senior Data Engineer to design, build, and optimize scalable data solutions supporting insights and innovation. You will work across the full data lifecycle from ingestion to deployment in an Agile setting.

The role requires hands-on coding in Python, PySpark, SQL, and hands-on experience with AWS services, Databricks, and DBT. You will contribute to production deployments with DevOps practices and collaborate in

Qualifications

• Extensive experience in building data ingestion frameworks and scalable data pipelines.

Responsibilities

• Design, develop, and manage CI/CD pipelines for data solutions.
• Perform data mapping and integration between source and target systems.
• Build and optimize data and AI solutions with data pipelines, modeling, and performance tuning.

Skills

Python

PySpark

SQL

AWS

Databricks

CI/CD

Git

Jenkins

DBT

Airflow

Spark

Scala

Hadoop

Data governance

Tools

Git

Jenkins

Apache Subversion

DBT

Job description

EY - GDS Consulting - AI And DATA - Data Engineer-Senior

Other locations: Anywhere in Country

Date: Oct 6, 2026

Requisition ID: 1715923

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

The Opportunity:

Join our dynamic team as a Senior Data Engineer, where you will play a critical role in designing, building, and optimizing scalable data solutions that drive business insights and innovation. You will work with cutting-edge technologies in a collaborative Agile environment, contributing to the full data lifecycle from ingestion to transformation and deployment.

Key Responsibilities:

• Design, develop, and manage robust CI/CD pipelines to streamline the product development lifecycle and ensure seamless deployment of data solutions.
• Perform data mapping, and integration between diverse source and target systems to support analytics and business intelligence needs.
• Build and optimize Data & AI solutions, including data engineering pipelines, data modeling, and performance tuning, with 5-8 years of relevant experience.
• Develop high-quality, production-level code primarily in Python, PySpark, and SQL, ensuring maintainability and scalability.
• Implement enterprise-scale production deployments, applying DevOps best practices, with hands‑on experience in Git version control.
• Collaborate effectively within Agile teams, contributing to sprint planning, reviews, and continuous improvement.
• Apply strong knowledge of Data Governance and Data Quality standards to maintain data integrity and compliance.

Technical Skills & Experience:

• Extensive experience in building data ingestion frameworks and scalable data pipelines.
• Proven expertise in AWS cloud services including S3, EC2, Glue, Lambda, and Secrets Manager for secure and efficient data processing.
• Hands‑on experience with Databricks for unified analytics and collaborative data engineering.
• Proficient in DBT (Data Build Tool) for data transformation and modeling within modern data stacks.
• Skilled in orchestrating workflows using Apache Airflow to automate complex data pipelines.
• Strong programming skills in Python, PySpark, Spark, and Scala for big data processing.
• Experience with software version control and CI/CD tools such as Git, Jenkins, and Apache Subversion.
• AWS / Databricks certifications or equivalent professional technical certifications are highly desirable.
• Familiarity with cloud and enterprise integration technologies.
• Demonstrated ability to write efficient Spark jobs and optimize performance in large‑scale environments.
• Excellent analytical skills with deep knowledge of SQL and data querying.
• Minimum 3 years of experience working in very large data warehousing environments.
• Strong communication skills, both written and verbal, to effectively collaborate with cross‑functional teams.
• At least 3 years of experience with data warehouse architectures, ETL/ELT processes, and reporting/analytics tools.
• Experience in Python and/or Java development in data engineering contexts.
• Familiarity with Big Data ecosystems including EMR, Hadoop, Databricks, Hive, and Pyspark.

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