Databricks Data Engineer
Databricks Data Engineer
Posted 6 days ago
SENIORITY
Lead
About the role
- Develop and maintain scalable and efficient data pipelines to ensure seamless data flow across various systems address any issues or bottlenecks in existing pipelines.
- Implement robust data checks to ensure the accuracy and integrity of data. Summarize and validate large datasets to ensure they meet quality standards.
- Monitor data jobs for successful completion. Troubleshoot and resolve any issues that arise to minimize downtime and ensure continuity of data processes.
- Regularly review and audit data processes and pipelines to ensure compliance with internal standards and regulatory requirements
- Familiar with working on Agile methodologies - scrum, sprint planning, backlog refinement etc.
- 4-9 years experience on Data Engineering role working with Databricks & Azure Cloud technologies.
- Bachelors degree in computer science, Information Technology, or related field.
- Strong proficiency in PySpark, Python, SQL.Strong experience in data modeling, ETL/ELT pipeline development, and automation
- Proficient in working on Azure cloud components Azure Data Factory, Azure Databricks, Azure Data Lake etc.
- Experience with data modeling, ETL processes, Delta Lake and data warehousing.
- Experience on Delta Live Tables, Autoloader & Unity Catalog.
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
