LiveHybridFull-timeApply by 1 Nov 2026
Technical Lead
Pune, Maharashtra, India
- Experience
- 7–10 years
- Employment
- Full-time
- Work mode
- Hybrid
- Salary
- ₹7.4 L–20.6 L / year
- Deadline
- Apply by 1 Nov 2026
- Posted
- 2025-04-24
Required skills
| Skill | Experience | Level |
|---|---|---|
| Python | 4+ years | Advanced |
| PySpark | 3+ years | Not specified |
| Azure Data Factory | 2+ years | Intermediate |
| Power BI | 2+ years | Intermediate |
| Data Lake | 2+ years | Intermediate |
About the role
Experience: 7 to 10 Years
Location: Pune / Chennai (Hybrid Mode)
Job Type: Full-Time / Permanent
Job Summary:
We are looking for a highly skilled and experienced Senior Data Engineer with expertise in Python, PySpark, Azure Data Factory (ADF), Azure Databricks, and Power BI. The ideal candidate will play a key role in designing, building, and maintaining scalable data solutions and pipelines on Azure cloud platform, enabling effective business intelligence and analytics.
Key Responsibilities:
- Design and develop data ingestion and transformation pipelines using Azure Data Factory and Azure Databricks.
- Implement complex ETL/ELT workflows using PySpark and Python to support analytical and reporting requirements.
- Collaborate with business analysts, data scientists, and BI developers to understand data requirements and deliver scalable solutions.
- Develop, manage, and optimize data models and datasets for Power BI reporting.
- Work on data cleansing, data integration, and performance optimization tasks.
- Ensure data quality, security, and governance in compliance with enterprise standards.
- Troubleshoot and debug production issues and provide timely resolutions.
- Follow best practices in coding, testing, and deployment within a CI/CD framework.
- Mentor junior team members and guide best practices in data engineering and cloud technologies.
Required Skills & Qualifications:
- 7–10 years of professional experience in data engineering or data platform development.
- Strong proficiency in Python and PySpark.
- Hands-on experience in Azure Data Factory for orchestrating data pipelines.
- Proficient in Azure Databricks for large-scale data processing and transformations.
- Strong experience with Power BI for data visualization and reporting.
- Solid understanding of data warehousing concepts, data lakes, and lakehouse architecture.
- Familiarity with DevOps tools, Git, and CI/CD pipelines for data projects.
- Strong SQL skills and experience working with structured and semi-structured data.
- Excellent communication and stakeholder management skills.