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Saur Energy International Linkedin · Posted 5d ago

Data Engineer

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Indexed description

You’ll Make a Difference By

  • 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.

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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.

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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

We’ll Support You With

  • Flexible and hybrid working opportunities
  • A diverse, inclusive, and collaborative culture
  • Continuous learning and development opportunities
  • An attractive and competitive compensation package.

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