Sr Data Engineer

Roles and Responsibilities: .

• Tests, monitors, manage and validate data warehouse activity including data extraction, transformation, movement, loading, cleansing, and updating processes
• Building and maintaining optimized and highly available data pipelines that facilitate deeper analysis and reporting
• Collaborate with stakeholders to understand, define and document business applications, data sources/relationships, and needs (metrics, dimensions, charts and dashboards).
• Analyze and Identify new data sources as needed per stakeholder requirements.
• Working closely with analytics team and other business stakeholders to create data processing frameworks that help the business make sense of growing data
• Manage and monitor existing data pipelines and work with other team members to ensure best practices for ETL and data warehousing
• Work on optimization of data storage and processing infrastructure to reduce costs
• Facilitate integration of different BI tools as needed by business stakeholders
• Assist in the design and documentation of data infrastructure and technologies

• Proficient in languages: Python.
• Minimum 2+ years’ experience as Data Engineer
• Experience in AWS Stack - Glue, Athena, Quick sight, RDS, Redshift, Kafka , pySparkExperience setting up data pipelines, archiving data, data lakes
• Bachelors or Master’s degree in computer science/Maths/statistics or related field
• Expertise with designing complex Data Models and Data Engineering solutions
• Write complex SQL for processing raw data, data transformations as well as data validations
• Experience with infrastructure as code using shell scripting
• Hands on experience in working with big data on AWS environments including cleaning/transforming/cataloging/mapping etc.
• Experience in setup of data warehouse using Amazon Redshift, creating Redshift clusters and perform data analysis queries
• Experience in ETL and data modeling on AWS ecosystem components - AWS Glue, Redshift, DynamoDB