Staff Data Engineer

About Us

With electric vehicles expected to be nearly 30% of new vehicle sales by 2025 and more than 50% by 2040, electric mobility is becoming a reality. ChargePoint (NYSE: CHPT) is at the center of this revolution, powering one of the world’s leading EV charging networks and a comprehensive set of hardware, software and mobile solutions for every charging need across North America and Europe. We bring together drivers, businesses, automakers, policymakers, utilities and other stakeholders to make e-mobility a global reality.

Since our founding in 2007, ChargePoint has focused solely on making the transition to electric easy for businesses, fleets and drivers. ChargePoint offers a once-in-a-lifetime opportunity to create an all-electric future and a trillion-dollar market.

At ChargePoint, we foster a positive and productive work environment by committing to live our values of Be Courageous, Charge Together, Love our Customers, Operate with Openness, and Relentlessly Pursue Awesome. These values guide how we show up every day, align, and work together to build a brighter future for all of us.

Join the team that is building the EV charging industry and make your mark on how people and goods will get everywhere they need to go, in any context, for generations to come.

Discover what it’s like to help build the fueling network of the future - check out our Engineering Blog.

Reports To

Senior Engineering Manager 

What You Will Be Doing

As a Staff Data Engineer at ChargePoint , you will play a crucial role in designing, building, and maintaining our data infrastructure. You will collaborate closely with cross-functional teams to ensure the availability and reliability of data for various analytical and reporting needs. If you are passionate about data engineering, excited to tackle challenges, and have a strong background in developing robust data pipelines, we want to hear from you.

What You Will Bring to ChargePoint:

• Data Pipeline Development: Design, build, and optimize data pipelines to ensure the efficient and scalable flow of data from source to destination.
• Problem Solving: Demonstrate strong problem-solving and logical reasoning skills to address complex data engineering challenges.
• Team Collaboration: Collaborate effectively with cross-functional teams and be a proactive team player.
• Programming: Utilize your programming skills to develop and maintain data pipelines, focusing on reliability and performance.
• Agile Environment: Thrive in an agile work environment, adapting to changing requirements and priorities.
• Python: Leverage your proficiency in Python programming to develop data solutions.
• NLP Understanding: Demonstrate an understanding of Natural Language Processing (NLP) algorithms and the ability to implement them.
• AWS Stack: Possess strong experience with the AWS data stack, including services like [list relevant AWS services].
• Big Data Technologies: Hands-on experience with PySpark, Apache Spark, and CI/CD implementation using Terraform.
• Snowflake and dbt: Experience in building ELT pipelines using Snowflake and dbt.
• BI Tools: Familiarity with BI tools such as PowerBI OR Tableau for data visualization and reporting.
• Leadership and Mentorship: Demonstrated ability to lead and mentor junior team members, providing guidance, coaching, and support in their professional growth and development.
• Architectural Design: Extensive experience in designing and architecting complex data solutions, including data lakes, data warehouses, and streaming data architectures. Ability to define and implement data architecture best practices to ensure scalability, reliability, and performance.
• Cross-Functional Collaboration: Strong ability to collaborate with cross-functional teams, including product management, engineering, and business stakeholders, to understand requirements, define solutions, and drive successful implementation of data projects.

Requirements:

• - Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
• -Minimum of 8-12 years of professional experience in data engineering, with a focus on designing, implementing, and optimizing data solutions at scale.
• -Proven ability to design and architect complex data solutions, including data lakes, data warehouses, and streaming data architectures. Experience in developing scalable, resilient, and high-performance data pipelines and systems.
• - Strong problem-solving skills and logical reasoning.
• - Proficiency in Python programming.
• - Knowledge of NLP algorithms and their implementation.
• - Experience with the AWS data stack.
• - Hands-on experience with PySpark, Apache Spark, and CI/CD using Terraform.
• - Familiarity with Snowflake and dbt for ELT pipelines.
• - Data modeling expertise.
• - Experience with BI tools like PowerBI and Tableau.
• - Strong understanding of data quality best practices.

Location

Bangalore, India

We are committed to an inclusive and diverse team. ChargePoint is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status.

If there is a match between your experiences/skills and the Company needs, we will contact you directly.

ChargePoint is an equal opportunity employer. 
Applicants only - Recruiting agencies do not contact.