Data Engineer - Databricks Unified Data Analytics
Summary
Designs and maintains Databricks-based data pipelines and ETL processes using PySpark and SQL to ensure clean, accessible data for analytics and reporting.
As a Data Engineer, you will design, develop, and maintain data solutions that facilitate data generation, collection, and processing. Your typical day will involve creating data pipelines, ensuring data quality, and implementing ETL processes to migrate and deploy data across various systems. You will collaborate with cross-functional teams to enhance data accessibility and usability, contributing to the overall data strategy of the organization.
Responsibilities
- Expected to be an SME.
- Collaborate and manage the team to perform.
- Responsible for team decisions.
- Engage with multiple teams and contribute on key decisions.
- Provide solutions to problems for their immediate team and across multiple teams.
- Develop and optimize data pipelines to ensure efficient data flow and processing.
- Monitor and troubleshoot data quality issues, implementing corrective actions as necessary.
- Document data processes and workflows to ensure clarity and compliance with best practices.
Qualifications
- 5 years of experience in Databricks Unified Data Analytics Platform.
- Experience with Python (Programming Language).
- Strong understanding of data modeling and database design principles.
- Experience with ETL tools and data integration techniques.
- Familiarity with cloud platforms and services related to data engineering.
- Proficient in data warehousing concepts and practices.
Must have and Good to have skills
- Databricks (Unity Catalog, Delta Live Tables, Auto Loader)
- Python, Pyspark
- SQL
- Azure Data Factory