Solution Architect - Data Engineer
At a glance
Mid-level Data Engineering role at KSB. Pune · full-time.
Pay not stated Data Engineering salary
dataroles summary, based on the employer's posting.
What you'll do
- Build and grow data pipelines and a data lake, using Python, Apache Spark and Databricks
- Set engineering standards and create reusable frameworks for dependable data solutions
- Support data modeling, integration and transformations that feed analytics and reporting
- Improve automation, monitoring and CI/CD, while keeping production pipelines reliable and maintainable
- Shape platform architecture and strategy, and connect data platform work with engineering, analytics and business teams
What you bring
- Strong programming ability, preferably in Python, with code that is clean, testable and production-ready
- Strong SQL skills and practical experience with Spark, ideally using Databricks
- Knowledge of lakehouse concepts, medallion architecture, data modeling and governance
- Experience running CI/CD pipelines and deploying, monitoring and maintaining data services in production
Who this fits
This mid-level role suits someone who can take data engineering work from planning through production and communicate across technical 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
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