Senior Data Engineer (Macedonia)

About the role

We are expanding our Data Engineering practice and need a senior‑level engineer to design, automate, and scale modern lakehouse and warehouse platforms on Azure, AWS, or GCP. The role partners with product managers, analysts, and data scientists to deliver governed, high‑quality data for batch and streaming use‑cases while leading proof‑of‑concepts, pre‑sales activities, and reusable framework development.

Key responsibilities

• Drive end‑to‑end data‑platform projects using Databricks, Microsoft Fabric, Snowflake and associated cloud services.
• Build and optimise ETL/ELT pipelines (batch, micro‑batch, real‑time) with Python/PySpark, dbt, Airflow, Kafka/Flink and cloud‑native tools.
• Automate deployment of data stacks via Git‑based CI/CD, ensuring observability and cost‑control.
• Implement data‑governance controls (GDPR‑compliant PII handling, lineage, quality tests) using Unity Catalog, Purview or Fabric governance.
• Mentor mid‑level engineers, codify best practices and contribute to architecture standards and run‑books.
• Troubleshoot production workloads, improve performance and maintain documentation for models and dictionaries.

Required profile

• 5+ years of data‑engineering experience, with at least 3 years in a cloud environment (AWS, Azure or GCP).
• Expert knowledge of data‑warehouse modelling concepts such as star/snowflake, Data Vault and lakehouse.
• Hands‑on experience with Databricks (Spark/Delta Live Tables), Microsoft Fabric (OneLake, Data Pipelines) or Snowflake, including performance tuning and cost optimisation.
• Proven track record building both batch and streaming pipelines.
• Strong Python and SQL skills.
• Solid grasp of CI/CD (GitHub Actions, Azure DevOps or similar) and Infrastructure‑as‑Code (Terraform or CloudFormation).
• Familiarity with DataOps, observability tools (Great Expectations, Monte Carlo, Prometheus/Grafana) and security best practices.

Required skills

• Python
• PySpark
• SQL
• Databricks
• Microsoft Fabric
• Snowflake
• Azure
• AWS
• GCP
• ETL/ELT
• dbt
• Airflow
• Kafka
• Flink
• GitHub Actions
• Azure DevOps
• Terraform
• CloudFormation
• Great Expectations
• Monte Carlo
• Prometheus
• Grafana