Senior AWS Data Engineer

EY GDS –Dataand Analytics (D&A) – AWSDataEngineer- Senior

As part of our EY-GDSData& Analytics (D&A) team, you will help clients solve complex business challenges usingdata-driven solutions. Our work spans across industries such as Banking, Insurance, Manufacturing, Healthcare, Retail, Supply Chain, Finance, and more. We help organizations unlock insights, modernize theirdataecosystems, and enable scalable analytics platforms.

The Opportunity

We are looking for skilled AWSDataEngineers with strong hands-on experience inPySpark, SQL, ETL pipelines, AWS services, and moderndatalakehouse/lake architectures. This is an excellent opportunity to join a fast-growing D&A practice within EY, working on high-impact, enterprise-scaledataprojects.

Key Responsibilities

• Develop,optimize, and deploy scalable ETL/ELT pipelines usingPySpark, SQL, and AWS services.

• Build and managedatalakehousesolutionsleveragingAWS S3, Glue, Iceberg, and other AWS-native components.

• Migrateon ‑ premisesETL workloads to modern AWS-based architectures with a focus on performance, reliability, and cost efficiency.

• Strong hands-on experience inDatabricks (PySpark, Delta Lake, Delta Live Tables, UnityCatalog).

• Implement metadata-driven ingestion frameworks and medallion/layered architecture (Bronze/Silver/Gold).

• Work on orchestration frameworks such as Astronomer (Airflow), AWS Step Functions, or AWS-managed workflows.

• Design andoptimizeSpark-baseddataprocessing jobs for high throughput.

• Followdatawarehouse (DW) concepts and best practices formodelinganddataintegration.

• Collaborate withdataanalysts,datascientists, and BI engineers for seamlessdatadelivery.

• Perform code reviews, troubleshoot issues, and ensure end-to-enddataquality.

• (Optional) LeverageDatabricks forPySpark, Delta Lake, Lakehouse, or workflow orchestration where applicable.

Skills and Attributes for Success

• 4+ years of total IT experience with at least 2+ years in AWS-baseddataengineering.

• Strong hands-on experience in:

• PySpark, SQL, Python

• ETL pipeline development

• Databricks

• AWS services: S3, Glue, Lambda, Step Functions, CloudWatch

• Unix/Linux environments

• Iceberg table format

• Astronomer (Airflow) or other orchestration tools

• Experience with structured andsemi ‑ structureddataformats such as Parquet, JSON, CSV, XML.

• Understanding ofdatawarehousing concepts, star/snowflake schemas, and dimensionalmodeling.

• Good knowledge of CI/CD, version control (GitHub, Azure DevOps, Jenkins).

• Strong analytical, troubleshooting, andproblem ‑ solvingskills.

• Ability to work independently and collaborate with stakeholders to deliverhigh ‑ qualitysolutions.

• (Optional but good to have) Experience working withDatabricks, Delta Lake, or UnityCatalog.

To Qualify, You Must Have

• Bachelor’s orMaster’s degree in Computer Science, IT, or related field.

• 4–7 years of industry experience indataengineering.

• Production-grade experience building and managing AWSdatapipelines.

• Hands-on experience with Agile/Scrum delivery models.

• Strong communicationand stakeholder management skills.

• Proactive,self ‑ drivenapproach with ownership of deliverables.

Ideally, You'll Also Have

• Client-facing and stakeholder management experience.

• Experience working in large-scale, multi-environmentdataplatforms.

What We Look For

Technically strong, curious, and adaptable professionals who enjoy solving challengingdataproblems and continuously learningnew technologiesin a fast-moving environment.

What Working at EY Offers

• Opportunities to work on diverse, meaningful, and industry-leading projects.

• Coaching, learning programs, and a personalized growth and development plan.

• Exposure to a collaborative, interdisciplinary work culture.

• Flexibility to manage your work in the way that suits you best.

• Supportive colleagues and a global environment for continuous knowledge exchange.