Senior Software Engineer ( UI Backend and Data Pipeline Engineer)

The Impact:We stand at the crossroads of innovation through Data Products to bring a competitive advantage to our business through the delivery of automotive forecasting solutions. Your work will contribute to the growth and success of our organization and provide valuable insights to our clients.

Whats in it for you:We are looking for an innovative and mission-driven software/data engineer to make a significant impact by designing and developing AWS cloud-native solutions that enable analysts to forecast long and short-term trends in the automotive industry. This role requires cutting-edge data and cloud-native technical expertise as well as the ability to work independently in a fast-paced, collaborative, and dynamic work environment.

Responsibilities:

• Design, develop, and maintain scalable data pipelines, including complex algorithms.
• Build and maintain UI backend services using Python, C#, or similar, ensuring responsiveness and high performance.
• Ensure data quality and integrity through robust validation processes.
• Strong understanding of data integration and data modeling concepts.
• Lead data integration projects and mentor junior engineers.
• Collaborate with cross-functional teams to gather data requirements.
• Collaborate with data scientists and analysts to optimize data flow and storage for advanced analytics.
• Take ownership of the modules you work on, deliver on time and with quality, and ensure software development best practices.
• Utilize Redis for caching and data storage solutions to enhance application performance.

What Were Looking For:

• Bachelor's degree in Computer Science or a related field.
• Strong analytical and problem-solving skills.
• 7+ years of experience in Data Engineering/Advanced Analytics.
• Proficiency in Python and experience with Flask for backend development.
• Strong knowledge of object-oriented programming.
• AWS proficiency is a big plus: ECR, Containerization, Batch, Step Functions, Redis, DynamoDB, Lambda.
• Experience with SQL and data warehousing.
• Experience with data manipulation libraries and analytical frameworks such as Pandas, Polars, and NumPy.
• Experience with GitLab CI/CD or similar tools for continuous integration and deployment.