About this role
Key Responsibilites
Hands-on Data Product development
- Implement scalable, reliable and reusable data pipelines using Azure Data Factory and Apache Airflow.
- Develop data transformations in Azure Databricks (PySpark / SQL) to create/extend data products following the Medallion Architecture layers:
- Bronze (raw ingestion)
- Silver (cleansed & conformed)
- Gold (business-ready data products)
- Optimize performance, cost, and reliability of data workloads.
- Raise important questions during business maturation in order to detect risks before development stage.
Technical Leadership
- Participate in architecture reviews and technical decision-making.
- Promote engineering excellence through code reviews and design reviews.
- Collaborate with Architects, Product Owners in data product technical maturation.
Support & Operations (Run Team Collaboration)
- Provide support to the Run/Operations team for production pipelines and data products for complex topics.
- Troubleshoot and resolve data incidents, failures, and performance issues
- Participate in incident management, root cause analysis, and post-mortems.
- Ensure proper handover, documentation, and operational readiness of developed solutions.
- Contribute to improving runbooks, monitoring, and operational processes.
Technical Skills Required
6+ years of experience in data engineering
Strong technical expertise with:
Python (PySpark)
SQL (advanced level)
Hands-on experience with Azure-based Data Platform including:
Databricks
Unity Catalog
Apache Airflow
Azure Data Factory
Reporting and BI tools (Power BI, Tableau or similar)
Solid understanding of data modelling fundamentals, main architectures and design patterns
Data Warehouse, Data Lake and Data Lakehouse architectures
Medallion architecture
Metadata-driven architecture
ETL/ELT design patterns
Understanding of:
Partitioning, optimization, and performance
Batch and streaming pipelines