Senior/Lead Data Engineer

📋 Description

• Design, develop, and enhance scalable ETL/data pipelines utilizing Azure Databricks.

• Automate data workflows through Azure Data Factory, Databricks, PySpark, and other relevant Azure services.

• Integrate various data sources into data lakehouse and data warehouse solutions to facilitate advanced analytics.

• Create SQL Warehouse views and data models for subsequent consumption and analytics applications.

• Convert intricate business requirements into scalable, dependable data products.

• Improve, diagnose, and sustain cloud-based data pipelines to guarantee performance, reliability, and data quality.

• Collaborate with cross-functional teams to ensure the timely delivery of data solutions.

⛳️ Requirements

• A minimum of 4 years of experience in Data Engineering.

• Demonstrated experience in building and optimizing scalable ETL/data pipelines, ideally on Azure Databricks.

• Familiarity with Azure Data Factory, Databricks, and PySpark.

• Extensive experience in integrating multiple data sources into data lakehouse/data warehouse architectures.

• Proficient SQL skills, including the design of data models and SQL Warehouse views.

• Experience in translating business requirements into scalable and reliable data solutions/products.

• Experience with cloud-based data platforms, preferably Azure.

• Strong problem-solving abilities with skills in troubleshooting and optimizing data pipelines.

• Knowledge of data quality, performance optimization, and reliability best practices.

• Experience working in cross-functional teams to deliver data solutions promptly.

🏝️ Benefits

• Flexible work arrangements.

• 20 working days per year as Non-Operational Allowance for personal recreation, fully compensated.

• Collaborative and supportive team culture.

• Truly competitive salary.

• Supportive HR and management team.