Assistant Manager

Manage small projects within the business analytics PMO. Ensure documentation and reporting standards are adhered to. Develop and deliver training sessions on project management best practices. Provide feedback and support to junior team members.

• Automate and maintain ETL pipelines using PySpark and AWS Glue to process and transform large volumes of data efficiently.
• Collaborate with team to understand data requirements and ensure data availability and quality.
• Write and optimize SQL queries for data extraction, transformation, and loading.
• Utilize Git for version control, ensuring proper documentation and tracking of code changes.
• Design, implement, and manage scalable data lakes on AWS, including S3, or other relevant services for efficient data storage and retrieval.
• Proficiency in Tableau for creating interactive dashboards and data visualizations.
• Automate workflows using AWS Cloud services like event bridge, step functions.
• Monitor and optimize data processing workflows for performance and scalability.
• Troubleshoot data-related issues and provide timely resolution.
• Stay up to date with industry best practices and emerging technologies in data engineering.

• 5-8 years of experience in ETL development with strong proficiency in Python (libraries such as Pandas, NumPy, SQLAlchemy).
• Bachelor’s degree in computer science, Data Science, or a related field. Master's degree is a plus.
• Strong proficiency in PySpark and Python for data processing and analysis.
• Proficiency in SQL for data manipulation and querying.
  
   
• Experience with version control systems, preferably Git.
• Familiarity with AWS services, including S3, Redshift, Glue, Step Functions, Event Bridge, CloudWatch, Lambda, Quicksight, DynamoDB, Athena, CodeCommit etc.
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills to work effectively within a team.
• Ability to manage multiple tasks and prioritize effectively in a fast-paced environment.