Trainee / Junior Data Engineer
Summary
Inforce, a software development company, is hiring a trainee/junior data engineer to build and maintain ETL/ELT pipelines in Python, write and optimize SQL, and load data from APIs, ERPs and CRMs into data warehouses. Day-to-day involves Airflow/Dagster orchestration, data quality checks, and preparing marts for BI dashboards under senior mentorship.
Inforce is a Software Development Company that provides a full range of top-quality IT services. Our mission is to develop first-class applications and Websites to provide our clients with the best solutions for maximizing their profits and converting their ideas into reality.
Why This Role Excites You
Build the Future of Data: Become one of the engineers shaping our Data Engineering direction and work on modern analytics and data platform solutions.
Work on real-world data pipelines feeding business-critical analytics.
Key Responsibilities
Build and maintain ETL/ELT pipelines in Python.
Write and optimize SQL queries for data transformation and reporting.
Extract data from ERP/CRM systems, REST APIs and client databases into our data warehouse.
Implement data quality checks: schema validation, tests, alerting.
Prepare data marts for BI dashboards (Metabase, Looker, Grafana).
Work with orchestration tools (Airflow, Dagster) under senior guidance.
Create and maintain technical documentation.
Collaborate with Backend, ERP and Analytics teams.
What We're Looking For
Solid Python fundamentals: functions, classes, working with files and APIs, basic pandas.
Strong SQL: joins, aggregations, window functions, basic query optimization — this is the core skill we test.
Understanding of what ETL is and why a data warehouse exists.
Git: branching, pull requests, working in a shared codebase.
Ability to explain your technical decisions, not just write code that runs.
Willingness to learn fast and ask questions early.
English: Intermediate (B1) or higher.
Nice to Have
Pet projects or data pipelines on GitHub — we value these more than certificates.
Docker basics (running services via docker-compose).
Exposure to Airflow, dbt or any orchestration tool.
PostgreSQL, ClickHouse or BigQuery experience.
Bash and Linux fundamentals.
Basic cloud awareness (AWS, Azure or GCP — any).
Commercial or internship experience in a data or backend role.
Not required: Kafka, Spark, Kubernetes, Terraform, dimensional modeling. You'll learn these here.
Why Join Us
Commercial projects with international clients in manufacturing, logistics, transportation and EdTech.
Personal mentor from day one - a structured onboarding plan, not "figure it out yourself".
Clear growth path: Trainee → Junior → Middle with defined criteria.
Exposure to the full modern data stack: Python, SQL, Airflow, dbt, cloud data warehouses.
Flexible full-time or part-time cooperation.
Remote-friendly environment.