What are the responsibilities and job description for the Data Engineer position at Saur Energy International?
You’ll Make a Difference By
You’ll Win Us Over By
You’ll Stand Out If You Have
- Designing, building, and maintaining scalable data products and data infrastructure on AWS
- Developing robust data pipelines using AWS-native services and integrating data across multiple application silos
- Supporting the automation, deployment, and operation of AI/ML workflows
- Defining data ingestion strategies, data formats and schemas, metadata/catalog integrations, federated data access, and end-to-end data product creation
- Enabling advanced analytics, AI/ML, and data-driven use cases by designing efficient data-access patterns and tooling (including support for LLM context engineering)
- Collaborating closely with Data Scientists, ML Engineers, and Product teams to translate business needs into scalable data solutions
- Actively participating in design discussions, technical reviews, and cross-team collaboration forums.
You’ll Win Us Over By
- Holding a Bachelor’s or Master’s degree in Computer Science, Engineering, or a related discipline
- Having 3 years of hands-on experience working with data at scale
- Strong programming skills in Python and SQL
- Strong understanding of databases (SQL and NoSQL), complex SQL queries and their performance across large, distributed databases.
- Experience in building and maintaining data pipelines
- Proven experience in building and maintaining CI/CD pipelines
- Solid understanding of SQL and NoSQL databases, complex SQL queries, and performance optimization across large, distributed systems
- Practical experience with Apache Spark (preferably PySpark)
- Clear communication skills and the ability to capture and define technical requirements effectively.
You’ll Stand Out If You Have
- Experience with TypeScript and/or JavaScript
- Working knowledge of databases such as PostgreSQL, DynamoDB, or similar technologies
- Strong collaboration experience with Data Scientists and Machine Learning Engineers
- Interest or hands-on exposure to MLOps and the AI product lifecycle
- Domain experience (or strong willingness to learn) in IoT, time-series data, automation systems, digital twins, or smart buildings technologies.
- Experience with Infrastructure as Code (ideally CDK, CloudFormation, Terraform) and cloud-native technologies in AWS (e.g. Lambda, Athena, Glue, SageMaker, S3, etc.)
- Experience with tools like EMR, Snowflake , AWS Glue
- Flexible and hybrid working opportunities
- A diverse, inclusive, and collaborative culture
- Continuous learning and development opportunities
- An attractive and competitive compensation package.