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Ernst & Young (EY)
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Gurugram · Hybrid · 8-11 Yrs · Oct 15
6 open roles4 posted in 7d6 in 30d
Hiring: Engineering
Job description
Hybrid
Responsibilities
- Technical Leadership & Platform Ownership Serve as the technical lead and design authority for AWS data engineering initiatives across multiple enterprise platforms. Own architectural decisions related to scalability, reliability, security, and cost optimization of AWS data platforms.
- Define and enforce engineering standards, coding patterns, and operational best practices for cloud data pipelines.
- Provide hands on technical guidance, design reviews, and code reviews for data engineers. AWS Data Platform Engineering Lead the design, development, and support of cloud native data pipelines using Amazon S3, AWS Glue (PySpark), MWAA (Apache Airflow), and AWS Step Functions.
- Drive on premises to AWS data platform migrations, including reverse engineering of legacy ETL workflows and re implementation using AWS native services. Re architect legacy Oracle Data Integrator (ODI)–based ETL processes into scalable PySpark based Glue jobs.
- Optimize Spark workloads for performance, memory usage, and cost efficiency in AWS Glue environments. Data Lake, Iceberg & Architecture Design Architect and implement enterprise AWS data lakes using Medallion architecture (Bronze, Silver, Gold).
- Design and manage Apache Iceberg tables to support incremental processing, schema evolution, and efficient data lake operations. Establish standardized ingestion, transformation, and consumption patterns across financial, mobility, and corporate datasets.
- Ensure data quality, reconciliation, lineage, and auditability across all layers of the data platform. Workflow Orchestration & Automation Lead orchestration strategy using MWAA (Managed Workflows for Apache Airflow).
- Design and implement Airflow DAGs in Python to orchestrate end to end workflows, including Glue jobs, validations, and downstream dependencies.
- Implement scheduling, retry logic, monitoring, and failure handling to ensure resilient and scalable pipelines.
- Integrate orchestration workflows with AWS services such as S3, Glue, Athena, Iceberg based data lakes, and downstream systems. Security, Infrastructure & AWS Networking Drive implementation of AWS security best practices, including IAM role design, least privilege access, encryption using AWS KMS, and secrets management.
- Lead configuration of AWS networking components such as VPC Endpoints (VPCE) to enable secure service to service communication.
- Manage infrastructure provisioning using Terraform, ensuring repeatable and auditable deployments across DEV, QA, and PROD environments. Coordinate with IAM, network, DevOps, and DBA teams to resolve access, firewall, and Oracle database connectivity challenges. Production Readiness, Operations & Support Own production readiness for AWS data platforms, including configuration, secrets, access controls, and deployment planning.
- Act as the escalation point for complex production issues, performing root cause analysis and permanent fixes.
- Implement logging, metrics, and alerting using Amazon CloudWatch to meet enterprise SLAs and availability targets.
- Support parallel run and hybrid architectures during migration phases to ensure business continuity. Automation, Compliance & Regulatory Enablement Design and oversee Python based automation solutions supporting operational efficiency and compliance initiatives (e.g., file retention and document processing).
Qualifications
- Bachelor’s degree in computer science, Engineering, or related field (or equivalent practical experience). 8-10 years of
- experience in Data Engineering with strong AWS exposure. Extensive hands on experience designing and leading AWS data engineering solutions. Proven experience leading or owning on premises to AWS data platform migrations. Advanced proficiency in Python and PySpark for data processing, automation, and orchestration. Strong
- experience with AWS Glue, Amazon S3, MWAA (Airflow), Step Functions, CloudWatch, and related services.
- Experience with Infrastructure as Code, preferably Terraform. Strong
- understanding of data engineering principles including ETL design, data modelling, and pipeline optimization. Demonstrated experience supporting enterprise, production grade data platforms. Good
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Job application FAQ
Last updated 27 October 2026
- How do I apply for WAM- AWS-Data-Engineer-Manager at Ernst & Young (EY)?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. Ernst & Young (EY) may attach structured assessments to interview rounds after you apply.
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- Is WAM- AWS-Data-Engineer-Manager remote or on-site in Gurugram, Haryana?
- This listing is marked hybrid with location Gurugram, Haryana. Confirm details on the job description before applying.
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- This is a mid-level WAM- AWS-Data-Engineer-Manager role. Key skills include Hybrid. Feedback AI highlights matched vs missing skills on your profile after signup.