You will collaborate closely with data scientists, analysts, and other engineers to deliver high-quality data solutions that drive business insights and improve decision-making.

Your work will directly impact our ability to leverage data effectively, enabling us to better serve our customers and achieve our business goals.

Key Responsibilities :

- Design and implement robust and scalable data pipelines using AWS services such as S3, Glue, Lambda, EMR, and Redshift for efficient data ingestion, processing, and storage.

- Develop and maintain ETL processes to transform raw data into usable formats for analysis and reporting, ensuring data quality and consistency.

- Build and optimize data models and schemas to support various analytical needs, enabling data-driven decision-making across the organization.

- Collaborate with data scientists and analysts to understand their data requirements and provide them with the necessary data infrastructure and tools.

- Implement data governance and security measures to protect sensitive data and ensure compliance with relevant regulations.

- Monitor and troubleshoot data pipeline performance, identifying and resolving issues to ensure data availability and reliability.

- Lead and mentor junior data engineers, providing guidance and support to help them grow their skills and contribute effectively to the team.

Required Skillset :

- Demonstrated expertise in designing and implementing data pipelines on AWS using services like S3, Glue, Lambda, EMR, Redshift, and Kinesis.

- Proven ability to develop and maintain ETL processes using Python and Spark for data transformation and loading.

- Strong understanding of data modeling principles and experience in designing data warehouses and data lakes.

- Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams.

- Ability to analyze complex problems, identify root causes, and implement effective solutions.

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

- 6-15 years of relevant experience in data engineering and related fields.