Lead Cloud Data Engineer
- 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.
- Experience in BFSI / Wealth Management domain.
- AWS Certification (Data Analytics Specialty, Solutions Architect, or Big Data).
- Familiarity with containerization (Docker, Kubernetes) and orchestration frameworks.
- Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field.
- Master’s degree preferred.
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