About this role

Lead the design, development, and deployment of large-scale data pipelines and solutions on AWS.
Provide technical leadership and mentorship to a team of data engineers, ensuring best practices in coding, architecture, and performance optimization.
Architect data lake and data warehouse solutions leveraging AWS Glue, Redshift, S3, Athena, EMR, and Lambda.
Drive development of ETL/ELT processes using PySpark, Python, and SQL.
Implement and enforce data governance, quality checks, and security standards across the platform.
Collaborate with business analysts, data scientists, and product teams to translate business requirements into scalable solutions.
Optimize cost and performance of AWS-based data workloads.
Troubleshoot production issues and ensure high availability of data pipelines.
Participate in sprint planning, backlog refinement, and Agile ceremonies as a technical lead.

13+ years of experience in Data Engineering, with at least 4+ years in a technical leadership role.
Strong expertise in AWS data services: Glue, S3, Redshift, Athena, Lambda, Step Functions, EMR.
Proficiency in PySpark, Python, and SQL for large-scale data processing.
Solid experience in data modeling (star, snowflake, dimensional modeling) and data lake/warehouse architectures.
Proven track record in leading and mentoring data engineering teams.
Strong understanding of Agile methodologies and CI/CD practices for data pipelines.

Lead Cloud Data Engineer

Key skills