Director/Head of Data Engineering and Business Intelligence

As the Director/Head of Data Engineering and Business Intelligence you will have the opportunity to design our overall data architecture and write the playbook on how we develop data driven insights in the company. You will be looked to as a thought leader for knowing when and how to use specific technologies that meet both performance and budgetary requirements and you will build a center of excellence establishing analytical rigor and scientific approaches to testing based on sound statistical theory. You will lead the organization in extracting rich insights from disparate data sets, build powerful visualizations and continuously look out for data driven business and process improvements. As the Director/Head of Data Engineering and Business Intelligence you will have an enormous opportunity to define the analytical framework and technologies guiding leadership decision making for new fast charging site locations. You'll be a key member of a high growth, VC-backed startup defining how to measure and improve the things that matter most to our customers. You will work with the product team to analyze feature launches and engagement trends to generate key insights for future improvements. And you will work with C-level leadership to ensure effective communication of business trends to our board of directors and key investors. 

Key Job Responsibilities
Design and implement an end-to-end, cost-effective data architecture spanning data ingest from disparate sources, storage,
scaling and vending to business stakeholders.

  • Retrieve and analyze data using a broad set of AWS technologies (e.g. Redshift and S3) and resources, knowing how, when, and which to use.
  • Extract, transform, and load data from many data sources using SQL, Scripting and other ETL tools.
  • Facilitate the selection, licensing, and implementation of a data visualization product such as Tableau.
  • Lead deep dive analysis of customer utilization behaviors, surface key insights and identify high value actions the growth team can action in product and marketing strategies.
  • Collaborate with executive leadership on charge point network site planning using 1st and 3rd party data to identify the highest value locations consistent with EVCS’ business strategy.
  • Partner closely with Product, Tech, and Operations leaders to define and analyze experiments, including any lessons learned and recommended changes to approach.
  • Define, measure and present metrics / automated reports on multiple products to senior leadership. Design new and enhance metrics, and continuously automate as needed to focus on highest leverage work.
  • Own and develop the mechanisms to prioritize a backlog of work across a variety of stakeholders. Escalate as needed to prioritize the most important work.
  • Establish an environment of self-service with stakeholders for simple or repeat requests through continuous development of knowledge bank, dashboards, or other mechanisms.

This position may be remote or hybrid based in our Los Angeles office.


Basic Qualifications

  • Bachelor’s degree in Engineering, Math, Finance, Statistics, or a related discipline
  • 6+ years of relevant work experience in data science, business analytics, business intelligence (BI), or comparable experience in big data environments.
  • 6+ years of experience in data mining and data-set preparation using SQL.
  • 6+ years of experience with Tableau Desktop or other relevant data visualization software.
  • Fluency and experience with statistical analytics and programming languages such as R, Python, Ruby, etc.

Preferred Qualifications

  • Master’s degree or higher in Statistics, Data Science, or an equivalent quantitative field
  • 8+ years of experience in a data engineer or BIE role with a technology company
  • Knowledge of data warehouse technical architecture, infrastructure components, ETL, and reporting/analytic tools and environments
  • Be self-driven, details-oriented, and show ability to deliver on ambiguous projects with incomplete or dirty data.
  • Experience using Cloud Storage and Computing technologies such as AWS Redshift, S3, Hadoop, etc.
  • Advanced knowledge of SQL, shell scripting, Python/R, and MS excel.
  • Strong understanding of BI technologies and their application including database warehousing and dashboarding
  • Experience communicating with senior management as well as with colleagues from computer science, operations research, and business backgrounds.

Job Application