Data Engineer

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.