Primeforge

• →Build and maintain data pipelines using Python and SQL
• →Develop integrations with internal systems and third-party APIs
• →Transform, validate, and model data for analytics and operational use
• →Investigate data-quality issues and improve reliability, observability, and performance
• →Write clean, tested, and maintainable code and contribute through Git-based workflows
• →Work within a US client's sprint cadence: standups, planning, tickets, pull requests, and delivery deadlines
• →Collaborate clearly in English across engineering, data teams, and business stakeholders

These are the baseline requirements for this role.

• 2-3 years professional software or data engineering experience
• Strong Python skills, including writing clean, modular, testable code
• Strong SQL skills beyond basic queries: joins, CTEs, window functions, agreegations, query debugging, and performance awareness
  
• Experience building or maintaining ETL/ELT pipelines, data integrations, or backend services
• Solid understanding of data quality: validation, reconciliation, error handling, and repeatable processing
• Demonstrates sound judgment using AI-assisted development tools: able to validate outputs, protect sensitive information, and retain ownership of delivered work
• Strong written and spoken English
• Able to work independently, ask good questions, and communicate blockers early.

You do not need every item below. Strong candidates will have depth insome of these areas and the ability to learn the rest

• Databricks, Spark, Delta Lake, or similar data-platform tools
• dbt, Airflow, Prefect, or other orchestration tools
• Cloud data services in Azure, AWS, or GCP
• Data warehouse and lakehouse environments
• Fast API or other Python API frameworks
• Docker and CI/CD workflows
• Data modeling for analytics oroperational reporting
• AI-enabled data applications, including RAG, Azure AI Search, LangChain, or LangGraph

Within your first months on a client team, you can:

• Pick up a ticket and move it to completion with appropriate guidance
• Write Python and SQL that another engineer can review and maintain
• Trace a data issue through a pipeline and explain what broke
• Communicate progress, risks, and questions clearly
• Earn trust through consistency, quality, and follow through

AI is part of modern software delivery at Primeforge. We provide engineers access to tools such as Claude and GitHub Copilot, with sufficient usage capacity to support real day-to-day work. We use AI to move faster: exploring unfamiliar codebases, drafting tests, accelerating documentation, debugging, generating implementation options, and reducing repetitive work. We also make room for engineers to experiment with emerging practices in agentic development and share what works with the wider team.

AI does not replace engineering judgment.

You are still responsible for understanding the systems you work in, validating output, protecting client information, writing maintainable code, and standing behind what ships. Strong engineers use AI to improve their leverage, not to avoid thinking.