Manager Data Engineering
Manager Data Engineering
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Job Description
We are looking for an experienced and dynamic Manager Data Engineering to lead the design development and optimization of scalable data pipelines and analytics platforms. This role demands a handson leader with deep expertise in AWS cloud services and Snowflake who can drive endtoend data engineering initiatives while mentoring a highperforming team.
You will collaborate closely with crossfunctional teams including Data Science Product and Engineering to deliver robust and secure data solutions that enable business insights and decisionmaking at scale.
Responsibilities:
Design and build scalable efficient and secure data pipelines and ETL/ELT processes using AWS services (Glue S3 Lambda Redshift Athena etc.) and Snowflake.
Implement and optimize data warehousing solutions in Snowflake to support BI analytics and ML workloads.
Ensure proper data modeling metadata management and version control for data assets.
Design and build scalable efficient and secure data pipelines and ETL/ELT processes using AWS services (Glue S3 Lambda Redshift Athena etc.) and Snowflake.
Implement and optimize data warehousing solutions in Snowflake to support BI analytics and ML workloads.
Ensure proper data modeling metadata management and version control for data assets.
Lead and mentor a team of data engineers; set goals conduct performance reviews and foster professional growth.
Drive the data engineering roadmap aligning technical initiatives with business priorities.
Collaborate with stakeholders to define data strategy architecture and scalable best practices.
Qualifications :
8 years of experience in Data Engineering with at least 2 years in a leadership/managerial capacity.
Proven expertise in AWS Data Stack (Glue S3 Redshift Lambda EMR etc.).
Handson experience with Snowflake including data modeling performance tuning and rolebased access.
Strong programming skills in Python SQL and Spark.
Familiarity with orchestration tools (Airflow Step Functions) and data versioning tools (DVC LakeFS).
Experience with CI/CD practices and InfrastructureasCode.
Excellent communication stakeholder management and crossfunctional collaboration skills.
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
