Description

You will build and maintain scalable data pipelines and full-stack solutions, leveraging AI tools to accelerate development, testing, and documentation.

Responsibilities

• Design and implement ETL/ELT processes and data integrations using Python, SQL, and cloud platforms.
• Develop and optimize data models for analytics and operational use cases.
• Validate and refine AI-generated code and queries to ensure accuracy, performance, and data quality.
• Integrate AI/ML capabilities, such as LLM APIs and automation tools, into data workflows.
• Document data flows, architectures, and AI-assisted processes while collaborating with stakeholders.

Required Skills

• 3+ years of experience in data engineering, analytics engineering, or full-stack development.
• Strong proficiency in Python, SQL, and relational or cloud data warehouses (Snowflake, BigQuery, Redshift).
• Hands-on experience with ETL/ELT tools like dbt, Informatica, or Airflow.
• Experience with AI-assisted development tools (LLMs, Claude, GitHub Copilot) and prompt engineering.
• Familiarity with Azure, AWS, or GCP cloud environments.
• Knowledge of data modeling concepts (star/snowflake schemas, dimensional modeling).
• Experience with version control (Git) and CI/CD practices.
• Ability to write and debug code in Scala or Python.

Preferred Skills

• Experience integrating AI/ML models or working with large language models in data workflows.
• Knowledge of data governance, lineage, and cataloging tools.

Key Skills

Education

Bachelor's or Master's degrees