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

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.

Data Engineering Manager

Key skills