- Be a technical lead for projects involving data processing and analytics at scale
- Design and implement algorithms to infer key transportation patterns from various data sources
- Ensure good architecture for StreetLight's products that can evolve over time
- Ensure high scalability and performance of software components and systems, with optimal use of machine resources
- Mentor junior engineers on technical design, coding and implementation
- Contribute to planning of sprints, with identification of technical tasks, and effort estimates
- Collaborate across Engineering teams (Applications, QA, Operations) as well as Product management and Services on projects
- Define and implement customized and/or cutting-edge solutions for customers, as needed
- BS/MS in Computer Science, Mathematics or an Engineering discipline from a top university.
- 3+ years of experience as a technical lead on software and/or data projects, building high-performance scalable systems.
- 10+ years of experience developing software and/or data products, with programming experience with Python as well as Java. Strong skills in algorithms, data structures, technical design and software architecture.
- 5+ years of experience in SQL and relational databases (PostgreSQL or BigQuery preferred), and strong understanding of relational concepts.
- Familiarity with cloud and big data technologies.
- Good data analysis skills, knowing what can/cannot be possible, and ability to visualize data in the best way possible.
- Understanding of techniques in data science (machine learning algorithms, regression analysis, etc.) is a plus.
- Strong communication skills - written, visual (presentations), and verbal.
- Ability to deliver adequate results on deadline, and make compromises to enable scalability and productization of algorithms.
- Geo-spatial skills are a plus.
- Knowledge of transportation data / industry is a plus.
- Quick learner, and a strong team player.
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Lead Data Engineer - San Francisco, United States - StreetLight Data
Description
StreetLight pioneered the use of Big Data analytics to shed light on how people, goods, and services move, empowering smarter, data-driven transportation decisions. The company applies proprietary machine-learning algorithms and data processing resources to measure travel patterns of vehicles, bicycles and pedestrians that enable complex transportation problem solving using analytics available on SaaS platform, StreetLight InSight. Acquired by Jacobs as a subsidiary in February 2022, StreetLight continues to provide innovative digital solutions to help communities reduce congestion, improve safe and equitable transportation, and maximize the positive impact of infrastructure investment.StreetLight Data is seeking a creative, versatile, and motivated Lead Data Engineer to be part of our growing team. This team member will lead data engineering and data science projects to develop exciting new algorithms for our product, as well as help productize those algorithms into our scalable StreetLight InSight analytics platform. This position reports to the Director of Data Science.
This position requires at least 1 day per week in office at our San Francisco or Vancouver locations.
Here's What You'll Do
Here's What You'll Need
The base salary range for this position is $175,000 to $205,000 USD. This range reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
StreetLight Data is an equal opportunity/affirmative action employer. StreetLight provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.