Data Engineering Manager

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EY

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1989

💸 Finance

Finance • Consulting • Technology

EY is a global professional services firm, widely recognized for providing audit, tax, consulting, and advisory services. It focuses on helping its clients solve complex problems and transform their businesses using data and technology. EY is committed to building a better working world by enhancing trust in financial markets and economies globally. Its services include corporate finance advisory, transaction strategy, technology consulting, and more, catering to sectors such as health, energy, finance, government, and more. EY also emphasizes sustainability and innovation in its solutions.

📋 Description

• Lead and mentor a team of data engineers • Define and drive the overall data architecture strategy • Oversee the design and implementation of data ingestion frameworks and integration solutions • Develop and manage CI/CD pipelines • Collaborate closely with clients and internal stakeholders • Act as a trusted advisor to clients • Ensure adherence to data governance and security standards • Drive the adoption of DevOps/DataOps principles within the team • Manage project priorities and delivery timelines

🎯 Requirements

• 10-13 years of relevant experience in data architecture design and implementation • Proven leadership experience managing data engineering and architecture teams in complex enterprise environments • Deep expertise in AWS services including S3, EC2, Glue, Lambda, and Secrets Manager • Hands-on experience with Databricks for unified data analytics • Proficiency with DBT (Data Build Tool) • Skilled in Apache Airflow for workflow automation and pipeline management • Strong programming skills in Python, PySpark, Spark, and Scala • Experience with software version control and CI/CD tools such as Git, Jenkins, and Apache Subversion • AWS certifications or equivalent professional technical certifications are highly desirable • Familiarity with cloud and on-premises middleware and enterprise integration technologies • Expertise in writing and optimizing Spark jobs and architecting data warehouse solutions • Excellent analytical skills with advanced SQL knowledge • Experience managing large-scale data warehousing environments and complex ETL/ELT pipelines • Strong understanding of data modeling concepts, data governance, and data quality frameworks • Exceptional communication skills, with proven ability to engage and influence clients and stakeholders • Experience in Python and/or Java development within data engineering and architecture contexts • Familiarity with Big Data ecosystems including EMR, Hadoop, Databricks, Hive, and Pyspark.

🏖️ Benefits

• Competitive salary • Flexible working hours • Professional development budget • Home office setup allowance • Global team events