Description

Job description:

1. Collaborate with client stakeholders to gather requirements, structure solutions, and ensure high quality, timely delivery.
2. Experience working in the Databricks tech stack with strong proficiency in SQL, Python, and PySpark
3. Design and optimize data models, data marts, and Lakehouse/warehouse layers with strong focus on medallion architecture, query optimization, and performance engineering.
4. Build, orchestrate, and monitor scalable data pipelines on Databricks, ensuring reliable ingestion, transformation, CDC handling, and incremental load strategies.
5. Manage end to end pipeline operations including performance tuning, data quality monitoring, alerting, and issue resolution across production workloads.
6. Lead a project team of data engineers supporting multiple workstreams and provide technical leadership through code reviews, best practice guidance, reusable pattern creation, and mentorship to engineering team members.
7. Prepare and maintain project documentation to support project execution and delivery.

Expected work split

1. 50% Technical – Data modeling, hands-on coding, orchestration, and pipeline monitoring.
2. 50% Management– Client Collaboration, requirements gathering, designing technical solutions, presentations, global team management and mentoring.

Qualifications (Required):

1. 8-12 years’ experience in data engineering and analytics roles
2. Bachelor’s or Master's degree in analytics, computer science/engineering, economics, mathematics,  or related areas.
3. Experience building and maintaining ETL/ELT pipelines
4. Solid understanding of data warehousing concepts and dimensional data modeling
5. Familiarity with workflow orchestration tools such as Airflow or similar
6. Experience working with cloud data platforms or modern data infrastructure
7. Entrepreneurial hands-on approach to work. Demonstrated leadership ability and willingness to take initiative
8. Superior analytical and problem solving skills
9. Outstanding written and verbal communication skills
10. Effective time management and attention to detail
11. Hands on experience in using SQL, Python and Workflow Schedulers (Apache Airflow, Cron)
12. Experience in leading team and coordinating with internal / external stakeholders

Qualifications (Preferred):

1. Experience in using Cloud Platforms (AWS / GCP / Azure)
2. Experience in using Visualization tools (Tableau / Power BI)
3. Experience with Big Data Technologies (Hadoop, Hive, Hbase, Pig, Spark, etc.)

Key Skills

Education

Any Graduate