Role Summary
Lead the data engineering team responsible for developing and modernising enterprise data pipelines and transformation frameworks.
Key Responsibilities
Lead design and development of Databricks pipelines .
Review and optimise ETL/ELT architecture.
Develop complex business transformations.
Translate business logic into technical implementation.
Re-engineer existing pipelines and improve performance.
Mentor data engineers.
Ensure engineering best practices.
Collaborate with architects and delivery teams.
While sharing the profile of your resource, share the details below along with the updated LinkedIn ID
| Technology / Skill Area | Candidate Experience (Years) | Self Rating (Out of 10) | |
| 1 | Overall Years of Experience | ||
| 2 | Relevant Experience | ||
| 3 | Relevant Data Engineering Experience | /10 | |
| 4 | Databricks Development | /10 | |
| 5 | Apache Spark / PySpark | /10 | |
| 6 | ETL Pipeline Development | /10 | |
| 7 | ELT Architecture | /10 | |
| 8 | Delta Lake | /10 | |
| 9 | Azure Data Factory / Workflow Orchestration | /10 | |
| 10 | SQL (Advanced) | /10 | |
| 11 | Python Programming | /10 | |
| 12 | Data Modelling (Star/Snowflake) | /10 | |
| 13 | Performance Tuning & Optimisation | /10 | |
| 14 | Data Transformation Frameworks | /10 | |
| 15 | CI/CD for Data Pipelines | /10 | |
| 16 | Git / Version Control | /10 | |
| 17 | Data Quality & Validation | /10 | |
| 18 | Pipeline Monitoring & Logging | /10 | |
| 19 | Cloud Platform (Azure/AWS/GCP) | /10 | |
| 20 | Team Leadership / Mentoring | /10 | |
| 21 | Architecture & Solution Design | /10 | |
| 22 | Educational Qualification (Mention the course name with Passout Year ) | ||
| 23 | Certifications (List all the certifications and share the soft copy or screenshots of certificates - if any ) | ||
| 24 | Currently engaged in any project (If yes, when was the last project completed) |
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