Data Engineer Lead
SWIR Vision Systems
Data Science
Bengaluru, Karnataka, India
Posted on Mar 11, 2026
Job Summary:
As a Lead Data Engineer, you will play a crucial role in designing, building, and optimizing cloud-based data pipelines and platforms that support enterprise analytics, AI/ML, and business intelligence initiatives.
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onsemi (Nasdaq: ON) is driving disruptive innovations to help build a better future. With a focus on automotive and industrial end-markets, the company is accelerating change in megatrends such as vehicle electrification and safety, sustainable energy grids, industrial automation, and 5G and cloud infrastructure. With a highly differentiated and innovative product portfolio, onsemi creates intelligent power and sensing technologies that solve the world’s most complex challenges and leads the way in creating a safer, cleaner, and smarter world.
More details about our company benefits can be found here:
| We are committed to sourcing, attracting, and hiring high-performance innovators, while providing all candidates a positive recruitment experience that builds our brand as a great place to work. |
Experience: 7+ years in data engineering or related roles with hands-on experience in cloud data platforms.
- Education: Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent professional experience.
- Technical Skills: Strong SQL and Python skills for data transformation and automation. Experience with Snowflake, Databricks, or similar cloud data platforms. Familiarity with orchestration tools (Airflow, dbt, etc.) and data modeling tools (ERWin, E/R Studio). Understanding of data preparation for AI/ML use cases and BI reporting. Exposure to DevOps and agile development practices.
- Leadership & Delivery: Demonstrated ability to lead small teams or mentor junior engineers. Strong problem-solving skills and a proactive mindset. Ability to manage multiple priorities and deliver high-quality results on time.
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Job Responsibilities
Cloud Data Engineering: Develop and maintain scalable, high-performance data pipelines and workflows on cloud platforms such as Snowflake and Databricks.
- Data Modeling & Transformation: Implement dimensional, canonical, and data vault models using tools like dbt and ER modeling platforms to support analytics and reporting.
- Platform Development: Support the development and optimization of enterprise-scale data lakes and data warehouses (100+ TB) for global business operations.
- Data Quality & Governance: Collaborate with data governance teams to implement metadata management, data quality checks, and master data integration.
- Cross-Functional Collaboration: Work closely with data architects, product managers, and agile teams to deliver robust data solutions aligned with enterprise standards.
- Automation & Orchestration: Build and maintain automated ELT/ETL pipelines using tools like Airflow, Fivetran, dbt, and Python, to ensure reliability and efficiency.
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