Data Engineer
Summary
Lead a team of data engineers to design, optimize, and maintain AWS-based data platforms (S3, Glue, Snowflake) and Airflow workflows, ensuring stability, security, and alignment with data strategy.
Key Skills:
- Lead a team of data engineers in managing day-to-day BAU operations, production support, incident management, and platform stability.
- Strong AWS knowledge in terms of designing new architecture and providing optimized solutions for existing ones. (S3, Glue, DMS, MWAA, AMS, IAM).
- In-depth knowledge with respect to Snowflake and its architecture.
- Prefer prior Experience in BAU environment.
- Good knowledge on Airflow and MWAA.
- Hands-on experience in SQL/Python/Pyspark.
- Expertise in optimizing techniques in cloud environments.
- Should have the vision on data strategy and able to deliver the same.
- Should be able to lead the design and implementation of data management processes, including data sourcing, integration, and transformation.
- Able to manage and lead a team of data professionals, providing guidance, mentoring and foster a collaborative and innovative team culture focused on continuous improvement.
- To evaluate and recommend data-related technologies, tools, and platforms.
- Collaborate with IT teams to ensure seamless integration of data solutions.
- Should have experience in Implementing and enforcing data security protocols and ensure compliance with relevant regulations.
Required Qualifications:
- At least 8+ years of Data Engineer Experience
- Bachelor qualification in a computer science or STEM (science, technology, engineering, or mathematics) related field.
- At least 5+ years of recent hands-on professional experience (actively coding) working as a Lead handling support & production issue.
- 2+ experience with large scale datasets, data lake and data warehouse technologies such as AWS Redshift, Google BigQuery, Snowflake. Snowflake is highly preferred.