Data Engineer Lead
At a glance
Senior Data Engineering role at onsemi. Bangalore · full-time.
Pay not stated Data Engineering salary
dataroles summary, based on the employer's posting.
What you'll do
- Build and tune cloud data workflows on Snowflake, Databricks or comparable platforms
- Create dimensional, canonical and data vault structures for analytics and reporting
- Help develop large enterprise data lakes and warehouses supporting global operations
- Add metadata practices, quality checks and master data links with governance teams
- Automate ELT and ETL using Airflow, Fivetran, dbt and Python, while partnering with architects and agile teams
What you bring
- At least seven years in data engineering or a related role, including practical work with cloud data platforms
- A computer science or engineering degree, a related qualification, or equivalent professional experience
- Strong SQL and Python skills, plus experience with Snowflake, Databricks or similar platforms
- Experience leading a small team or coaching junior engineers
Who this fits
This senior lead role suits someone who can combine hands-on cloud data engineering with team guidance. The position is based in Bangalore, India.
From the employer
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.
#L1-LK1
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.
#L1-LK1
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.
#L1-LK1
Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.
Each morning you get everything that fits, strongest first.
Data Engineering
Find me workBy the team behind dataroles.