More jobs:
Job Description & How to Apply Below
Experience : 6 - 9 years
Location:
Gurugram (Hybrid)
Shift: 3 PM – 12 AM IST (Flexible)
We are looking for an experienced Azure Databricks / Data Lake Engineer to join our growing data engineering team. This role is ideal for someone who enjoys building scalable, high-performance data platforms and working closely with analytics and business stakeholders.
What You’ll Do:
- Design, build, and optimize batch & streaming data pipelines using Azure Databricks, PySpark, SQL, Delta Lake
- Implement Lakehouse & Medallion architecture with strong data quality and governance
- Manage Databricks work spaces, clusters, security (Unity Catalog, RBAC) and cost optimization
- Work on CI/CD pipelines and automate deployments
- Collaborate with BI, analytics, and product teams for end-to-end data & analytics delivery
- Drive best practices in performance tuning, monitoring, and scalability
What We’re Looking For:
- 7+ years of overall data engineering experience
- 3+ years hands-on experience with Azure Databricks
- Strong expertise in Python, SQL, Spark, Delta Lake
- Experience with Azure Data Factory, ADLS Gen2
- Solid understanding of data warehousing & dimensional modeling
- Ability to work in a fast-paced, stakeholder-driven environment
Good to Have:
- Databricks or Azure certifications
- BI tools exposure (Power BI / Tableau / Looker)
- Experience with on-prem to cloud data migrations
Interested candidates kindly share your resume at
Position Requirements
10+ Years
work experience
Note that applications are not being accepted from your jurisdiction for this job currently via this jobsite. Candidate preferences are the decision of the Employer or Recruiting Agent, and are controlled by them alone.
To Search, View & Apply for jobs on this site that accept applications from your location or country, tap here to make a Search:
To Search, View & Apply for jobs on this site that accept applications from your location or country, tap here to make a Search:
Search for further Jobs Here:
×