Develop Python data pipelines that build business data objects used to support applications.
Responsible for developing and maintaining high standards of software quality within the team.
Building and deploying CICD pipelines.
Implementing source to target mapping as pipeline code.
Responsibility for Unit and Integration testing.
Identifying and encourage areas for growth and improvement within the team.
Building engineering automations to improve development velocity and operational efficiency.

Extensive software development experience and solid working knowledge of OOP principles (typically 5+ years).
Experience in designing and developing software applications in Python (typically 4+ years).
Experience working with Git version control on medium to large teams.
Deploying software using CI/CD tools such as Github Actions, Azure Devops etc.
Experience with AWS components such as Lambda, Kinesis, Event Bridge, CloudWatch, CloudFormation, Dynamo, Fargate, S3, Sage Maker, IAM and RDS
Experience working with Snowflake.
Hands‑on experience with GenAI developer tools.
Practical usage of tools such as GitHub Copilot or Claude Code, or similar AI coding assistants to improve developer productivity, code quality, and delivery speed.
Ability to learn and adapt in a rapidly evolving space.
Demonstrates curiosity and continuous learning as GenAI tools, frameworks, and best practices evolve quickly.
Applied knowledge of GenAI tools in real use cases.
Proven experience applying GenAI to solve real business or engineering problems (e.g., data processing, automation, assistants, recommendations, or decision support).
Understanding of Lang Chain and Lang Graph frameworks.

Data Engineer, Digital Data & AI

Key skills