Senior Databricks Data Engineer

About us:

20 years on the Romanian IT market and still growing.

Part of the HN Services Group, with offices in France, Spain, Portugal, and Luxembourg, HN Services Romania is about building real careers, not just filling roles.

What you’ll find here:

• Digital transformation projects with real impact

• A wide range of technical roles across modern and legacy technologies (yes, COBOL is still very much alive)

• Exposure to diverse industries and international environments

• Continuous growth through our in-house software development training center (HN Training Institute)

💡We are currently looking for a Senior Databricks Developer responsible for designing, developing, optimizing, and operating data solutions on the Databricks platform.

The role contributes to the implementation and evolution of the organizational Data Lakehouse, developing data ingestion, transformation, processing, and delivery processes for reporting, advanced analytics, and AI/ML initiatives.

The person will have end-to-end responsibility for data flows and will act as a technical reference within the team.

Key Responsibilities

Data Development & Integration:

• Develop and maintain data ingestion, transformation, and publishing processes using Databricks and PySpark.
• Build and optimize ETL/ELT pipelines for large volumes of data.
• Implement Delta Lake structures and data models for operational and analytical consumption.
• Develop mechanisms for incremental processing, historization, and CDC (Change Data Capture).
• Integrate data from multiple sources, including Oracle, SQL Server, APIs, files, banking applications, etc.

Data Architecture & Modelling:

• Participate in defining the Data Lakehouse architecture.
• Propose scalable and high-performance data models.
• Contribute to the development of platform architecture and development standards.
• Ensure data traceability and consistency throughout the entire processing flow.

Data Quality & Operations:

• Implement automated Data Quality controls.
• Develop data reconciliation and validation processes.
• Configure process monitoring, alerting, and logging.
• Analyze and resolve production incidents.
• Manage reloads, reruns, corrections, and data recovery.

Optimization & Performance:

• Optimize PySpark and SQL processes for cost and performance.
• Identify and eliminate processing bottlenecks.
• Optimize Databricks resource consumption.
• Contribute to the automation of development and deployment processes.

Required Experience & Competencies:

• Minimum 5 years of experience in Data Warehouse development, Big Data, or enterprise data platforms.
• Minimum 2–3 years of hands-on experience with Databricks.
• Demonstrated experience in complex Data Warehouse, Data Mart, or Data Lake projects.
• Experience developing end-to-end data pipelines.
• Strong knowledge of Data Lakehouse architecture.
• Experience implementing historization, CDC, reconciliation, and Data Quality processes.
• Ability to take full ownership of technical deliveries and provide technical leadership to the team.

Mandatory Technical Skills

• Azure Databricks / PySpark
• Advanced SQL
• Delta Lake
• Git & Jira
• Data Modelling
• ETL / ELT
• Data Quality Frameworks
• Pipeline Orchestration

Nice-to-Have Technical Skills

• Azure Data Factory
• Kafka
• Event Streaming
• Advanced Python
• CI/CD
• Unity Catalog
• Data Governance
• Machine Learning on Databricks
• Qlik Sense

Banking Experience – Major Advantage

• Knowledge of Retail Banking products and processes.
• Experience with financial reporting and management reporting.
• Knowledge of risk, compliance, and regulatory reporting processes.
• Understanding of banking data flows and enterprise analytical ecosystems.

*Only eligible candidates will be contacted for further information and start of the recruitment process.