Databricks Lead – Delivery & Engineering
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Before you apply
LocationPune, Maharashtra; Hyderabad, Telangana
SeniorityLead
Experience10–12 yrs
DepartmentEngineering
Company size1,001–5,000 people
PostedApr 1, 2026 · 7mo ago
Verified live3d ago
At a glanceSummarised by Seekless from the posting.
10–12 years in data engineering
3–5 years hands-on Databricks experience
Deep expertise in Databricks, Apache Spark, Delta Lake
Strong hands-on experience with PySpark / Spark SQL
Experience designing Lakehouse architectures
Strong understanding of data modeling, data quality, and lineage
Knowledge of Databricks platform features
Cloud-native data engineering
Performance tuning & troubleshooting
Databricks Data Engineer Associate and Professional certifications
Skills
Databricks
Apache Spark
Delta Lake
PySpark
Spark SQL
CI/CD
Java
SQL
Streaming
Databricks Lead – Delivery & Engineering1
Lead hands-on Databricks delivery, ensuring adherence to CoE standards and best practices.
Key Responsibilities
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Lead Databricks engineering teams
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Build and optimize Spark & Delta Lake pipelines
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Implement Databricks Jobs, Workflows, CI/CD
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Optimize performance and DBU usage
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Contribute to Databricks accelerators and standards
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Design and implement end-to-end data platforms using Databricks Lakehouse
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Lead development of:
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Data ingestion (batch & streaming)
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Delta Lake data modeling (Bronze/Silver/Gold)
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Scalable ETL/ELT pipelines
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Optimize Spark workloads for performance and cost
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Ensure reliability, scalability, and observability of data pipelines
Experience
•
10–12 years in data engineering
•
3–5 years hands-on Databricks experience
Skills
•
Deep expertise in Databricks, Apache Spark, Delta Lake
•
Strong hands-on experience with PySpark / Spark SQL (core, SQL, streaming)
•
Experience designing Lakehouse architectures
•
Strong understanding of data modeling, data quality, and lineage
•
Databricks platform features
•
Cloud-native data engineering
•
Performance tuning & troubleshooting
Certifications (Preferred)
•
Databricks Data Engineer Associate and Professional