Senior Engineer - Data Engineering
Pune Full-time Senior Data Engineering
At a glance
Senior Data Engineering role at KSB. Pune · full-time.
Pay not stated Data Engineering salary
RoleData Engineering
SenioritySenior
LocationPune
EmploymentFull-time
PostedJun 2, 2026
Role brief
dataroles summary, based on the employer's posting.
What you'll do
- Build and grow scalable data pipelines and the data lake using Python, Spark and Databricks
- Set shared engineering practices and reusable frameworks, while keeping data solutions reliable and maintainable
- Support data modeling, integration and transformation for analytics and reporting needs
- Improve automation, monitoring and CI/CD, and contribute to platform architecture and long-term direction
- Connect data platform work with engineering, analytics and business teams
What you bring
- At least three years of company-based project or coding experience, plus a bachelor's degree in a related field
- Strong SQL and Python skills, with experience producing clean, testable code for production
- Practical Spark experience, preferably using Databricks, and knowledge of lakehouse and medallion architecture
- Experience running data pipelines in production and building CI/CD, with cloud experience such as AWS or Azure
Who this fits
This senior role suits an engineer who can own data work independently and communicate clearly across engineering and data teams. The position is based in Pune, India.
From the employer
Key Responsibilities
- Contribute to the design and development of scalable data pipelines and a growing data lake
- Build and extend data processing workflows using Python, Apache Spark, and Databricks
- Define technical standards, best practices, and reusable frameworks for data engineering
- Ensure data quality, reliability, performance, and maintainability across data solutions
- Support data modeling, data integration, and transformation processes for analytics and reporting
- Drive automation, monitoring, and CI/CD improvements to ensure operational excellence
- Collaborate across teams, acting as a technical interface between the data platform and engineering, analytics, and business stakeholders.
- Contribute to architecture decisions and long-term data platform strategy
Your Profile
- Outstanding programming experience, preferably in Python; ability to write clean, testable, production-grade code; able to write clean, testable, production-grade code
- Strong SQL skills and familiarity with structured and semi-structured data formats (JSON, Protobuf, Delta format)
- Hands-on experience with Apache Spark, ideally on Databricks, and understanding of the medallion architecture
- Solid grasp of data lakehouse principles, data modeling, and data governance concepts
- Experience building and maintaining CI/CD pipelines (e.g. GitLab CI); familiarity with IaC and deployment
- Cloud Platforms: Experience with AWS or comparable cloud providers; familiarity with Databricks as a managed Lakehouse platform
- Experience with event-driven architectures or streaming platforms (e.g. Kafka)
- Proven track record deploying, monitoring, and maintaining data pipelines and services in
production environments; experience with testing practices - Able to work autonomously and take ownership of tasks end-to-end
- Clear and concise communicator — comfortable working across engineering and data teams
Education & experieance
- Bachelor's degree in Software Engineering, Mathematics, Physics, or a related field
- 3 years of project/coding experience in a company
- Cloud experience:
- Databricks, AWS/Azure
- Staging, testing, Git, pipelines
- Distributed systems, data pipelines
- Python experience:
- Versioning, package management, requirements/environments
- Change data capture
- Data engineering experience:
- SQL
- Partitioning
- Data structures (tables, relations)
- Lakehouse
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