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

EY

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

EY

·

On-site

·

Full-time

·

3w ago

필수 스킬

Python

SQL

AWS

Linux

Azure

Spark

Airflow

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 GDS – Data and Analytics

  • D and A – AWS Data Engineer
  • Senior

As part of our EY-GDS Data & Analytics (D&A) team, you will help clients solve complex business challenges using data-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 their data ecosystems, and enable scalable analytics platforms.

The Opportunity

We are looking for skilled AWS Data Engineers with strong hands-on experience in Py Spark, SQL, ETL pipelines, AWS services, and modern data lakehouse/lake architectures. This is an excellent opportunity to join a fast-growing D&A practice within EY, working on high-impact, enterprise-scale data projects.

Key Responsibilities

  • Develop, optimize, and deploy scalable ETL/ELT pipelines using Py Spark, SQL, and AWS services.

  • Build and manage data lakehouse solutions leveraging AWS S3, Glue, Iceberg, and other AWS-native components.

  • Migrate on premises ETL workloads to modern AWS-based architectures with a focus on performance, reliability, and cost efficiency.

  • 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 and optimize Spark-based data processing jobs for high throughput.

  • Follow data warehouse (DW) concepts and best practices for modeling and data integration.

  • Collaborate with data analysts, data scientists, and BI engineers for seamless data delivery.

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

  • (Optional) Leverage Databricks for Py Spark, 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-based data engineering.

Strong hands-on experience in:

  • Py Spark, SQL, Python

  • ETL pipeline development

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

  • Unix/Linux environments

  • Iceberg table format

  • Astronomer (Airflow) or other orchestration tools

  • Experience with structured and semi structured data formats such as Parquet, JSON, CSV, XML.

  • Understanding of data warehousing concepts, star/snowflake schemas, and dimensional modeling.

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

  • Strong analytical, troubleshooting, and problem solving skills.

  • Ability to work independently and collaborate with stakeholders to deliver high quality solutions.

  • (Optional but good to have) Experience working with Databricks, Delta Lake, or Unity Catalog.

To Qualify, You Must Have

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

  • 4–7 years of industry experience in data engineering.

  • Production-grade experience building and managing AWS data pipelines.

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

  • Strong communication and stakeholder management skills.

  • Proactive, self driven approach with ownership of deliverables.

Ideally, You'll Also Have

  • Client-facing and stakeholder management experience.

  • Experience working in large-scale, multi-environment data platforms.

What We Look For

  • Technically strong, curious, and adaptable professionals who enjoy solving challenging data problems and continuously learning new technologies in 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.

EY | Building a better working world

EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.

Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.

Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

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EY 소개

EY

EY

Public

EY, previously known as Ernst & Young, is a British multinational professional services network based in London, United Kingdom. Along with Deloitte, KPMG and PwC, it is one of the Big Four professional services firms.

10,001+

직원 수

London

본사 위치

리뷰

3.4

10개 리뷰

워라밸

2.3

보상

3.7

문화

4.1

커리어

3.8

경영진

3.2

65%

친구에게 추천

장점

Good learning opportunities and career advancement

Supportive culture and kind people

Professional environment and good benefits

단점

Long working hours and poor work-life balance

Hectic and taxing work environment

Limited support for interns and technical growth

연봉 정보

31,254개 데이터

Mid/L4

Mid/L4 · Operations Research Analyst

1,738개 리포트

$142,571

총 연봉

기본급

$136,899

주식

-

보너스

$5,673

$100,128

$203,912

면접 경험

7개 면접

난이도

3.0

/ 5

소요 기간

14-28주

합격률

57%

면접 과정

1

Application Review

2

HR Screen

3

Hiring Manager Interview

4

Technical/Case Interview

5

Partner/Director Interview

6

Offer

자주 나오는 질문

Behavioral/STAR

Case Study

Technical Knowledge

Past Experience

Culture Fit