Data Engineering Manager
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Job Description
Data Engineering Manager overseeing scalable, enterprise-grade data solutions at EY. Leading a team and ensuring alignment with business objectives for advanced analytics.
Responsibilities:
- 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
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