AWS Data Engineering Manager

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. 

EY – Consulting – AWS Data Engineering Manager

The Opportunity

We are seeking an experienced and visionary AWS Data Engineering Manager to lead our data engineering initiatives within the Consulting practice and have about 7+ years of experience. This role is ideal for a strategic thinker with a strong technical foundation in AWS and data engineering, who can guide teams, architect scalable solutions, and drive innovation in data platforms. You will play a pivotal role in shaping data strategies, mentoring teams, and delivering impactful solutions for our clients.

Key Responsibilities

• Lead the design and implementation of scalable data pipelines using AWS technologies, supporting both batch and real-time data processing.
• Architect robust data lake solutions based on the Medallion Architecture using Amazon S3 and integrate with Redshift and Oracle for downstream analytics.
• Oversee the development of data ingestion frameworks from diverse sources including on-premise databases, batch files, and Kafka streams.
• Guide the development of Spark streaming applications on Amazon EMR and batch processing using AWS Glue and Python.
• Manage workflow orchestration using Apache Airflow and ensure operational excellence through monitoring and optimization.
• Collaborate with cross-functional teams including data scientists, analysts, and DevOps to align data solutions with business goals.
• Provide technical leadership, mentorship, and performance management for a team of data engineers.
• Engage with clients to understand business requirements, define data strategies, and deliver high-quality solutions.

Required Skills and Experience

• Proven leadership experience in managing data engineering teams and delivering complex data solutions.
• Deep expertise in AWS services including S3, Redshift, Glue, EMR, and Oracle.
• Strong programming skills in Python and Spark, with a solid understanding of data modeling and ETL frameworks.
• Hands-on experience with Kafka for real-time data ingestion and processing.
• Proficiency in workflow orchestration tools like Apache Airflow.
• Strong understanding of Medallion Architecture and data lake best practices.

Preferred / Nice-to-Have Skills

• Experience with Infrastructure as Code (IaC) using Terraform.
• Familiarity with additional AWS services such as SNS, SQS, DynamoDB, DMS, Athena, and Lake Formation.
• Knowledge of monitoring and alerting tools like CloudWatch, Datadog, or Splunk.
• Understanding of data security best practices for data at rest and in transit.

Qualifications

• BTech / MTech / MCA / MBA or equivalent.
• AWS certifications (e.g., AWS Certified Data Analytics – Specialty, AWS Certified Solutions Architect) are a plus.

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