Senior Data Engineer - EV Charging (711204) - New York - ref. c9131219

1. Lead data engineering projects from conception over testing & validation to development & rollout. Provide guidance and mentoring to junior data scientists and engineers and drive the adoption of best practices in data handling and analysis to ensure high data quality and valuable insights. 20%
2. Review gathered datasets of electric vehicle (EV) charging systems and analyze energy and electric power usage, general charging behaviors and user behaviors to derive data insights for optimization potential and build a unified view that supports automatic decision-making in near real time. 10%
3. Develop and maintain a robust testing environment; work with the team of engineers to evaluate the performance and accuracy of data models and algorithms specific to EV charging systems and design and implement testing methodologies that simulate real-world scenarios to ensure software reliability and data integrity under various usage and stress conditions. 17%
4. Design and construct data algorithms architectures based on gathered and analyzed data, ensuring scalability, reliability, and safety. 5%
5. Work with the data engineering team to design and deploy data-driven solutions that enhance the efficiency and accessibility of EV charging networks and support the iteration and improvement of smart EV charging software. 5%
6. Develop quantitative and qualitative analytical and research methods to support long-term energy resource planning for the companys systems. 5%
7. Apply advanced analytics and machine learning techniques including correlation analysis, neural networks, cluster analysis, time series analysis, and regression analysis to predict EV charging patterns, optimize grid performance, build proof-of concept-optimization algorithms for smart EV charging demonstrations and make automatic control decisions in near real time to enhance user experience. 10%
8. Provide strategic insights and contribute to the advancement of innovative solutions ensuring the organization remains at the forefront of industry knowledge and practices. 5%
9. Work closely with the developers and managing the design, and implementation of testing methodologies and building simulation tools and energy optimization algorithms in Python using Machine Learning, Operations Research, Linear Programming as well as data science tools including NumPy, Pandas, Scikit-Learn, TimescaleDB, Grafana, and PostgreSQL to ensure software reliability and data integrity under various usage and stress conditions. 9%
10. Serve as the designated expert within the organization, both internally and externally, with a focus on optimization, testing and research related to energy technology. 4%
11. Utilize cloud computing services including Google Cloud Platform (GCP), along with databases including PostgreSQL and Timescale DB, to collaborate with software developers, product managers, and external partners on designing and deploying data-driven solutions that enhance the efficiency and accessibility of EV charging networks. 5%
12. Work with customers and prospective partners to understand the problem statements and develop solutions, as well as work with product management and join planning meetings to develop energy data science roadmaps. 5%

This position requires two (2) years of experience in the job offered or related. Experience must include:

1. Utilizing cloud computing services including Google Cloud Platform (GCP), and databases including PostgreSQL and Timescale DB
2. Designing and deploying data-driven solutions that enhance the efficiency and accessibility of EV charging networks and supporting the iteration and improvement of smart EV charging software.
3. Applying advanced data analysis methods, and machine learning techniques including correlation analysis, neural networks, cluster analysis, time series analysis, and regression analysis to build proof-of-concept optimization algorithms for smart EV charging demonstrations.
4. Gathering datasets of electric vehicle (EV) charging networks, and analyzing energy and electric power usage and general charging behaviors to derive data insights for optimization potential.
5. Building simulation tools and energy optimization algorithms in Python using Machine Learning, Operations Research, Linear Programming, and data science tools including NumPy, Pandas, Scikit-Learn, and Grafana to assist in energy data analysis.

Please copy and paste your resume in the email body do not send attachments, we cannot open them and email them at candidates at (link removed) with reference #711204 in the subject line.

Thank you.