Data Engineer ( 2 to 5 Years)

Role Overview

We empower our people to stay resilient and relevant in a constantly evolving digital world. We’re looking for curious minds who are passionate about building scalable data platforms and enabling intelligent, data-driven solutions. If you enjoy solving complex problems and want to make a real impact today and in the future, you might be the perfect fit for our team.

Responsibilities

• 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.

Requirements

• 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.

Nice to 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 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

Skills

• Python
• SQL
• AWS
• Apache Spark
• CI/CD

Benefits

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