Glydways is reimagining public transit to make it more accessible and sustainable. They are seeking a Data Platform Engineering Lead to set the technical direction of their data stack, develop analytics solutions, and mentor a team of engineers.
Responsibilities:
- Own the technical roadmap for our data platform, balancing near-term delivery against long-term scalability
- Develop analytics and data accessibility solutions for internal engineering teams as well as external stakeholders
- Set a high bar of technical excellence for data quality, validation, governance, and observability across the data lifecycle
- Mentor and grow a team of analytics engineers and data engineering by guiding technical decisions, reviewing code and designs, and supporting career development
- Partner with engineering leadership on planning, prioritization, and headcount
- Collaborate cross-functionally with both technical and non-technical customers to platform new data analytics workloads
- Research, evaluate, and integrate cutting-edge big data technologies to enhance our platform capabilities and influence build-vs-buy decisions
Requirements:
- Degree in Computer Science, Analytics, Engineering or a related field
- Management experience building and leading engineering teams is a must
- Extensive experience building and operating production data platforms, with a track record of technical ownership over major systems
- Proficiency with big data technologies (e.g., Spark, Hadoop, Hive, dbt)
- Proficiency with workflow orchestration tools (e.g., Airflow, Argo Workflows)
- Proficiency with multi-language build systems (e.g., Bazel, CMake) and containerization technologies (e.g., Docker, Kubernetes)
- Proficiency with cloud platforms (e.g., AWS, Azure, GCP)
- Expertise in Python and Shell
- Expertise in SQL and/or SQL-like query languages
- Expertise in version control systems (e.g., Git)
- Expertise in configuration languages (e.g., YAML, CUE)