Data Platform Engineering Lead

🕒 June 22

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 18%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Glydways

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2016

🚗 Transport

🤖 Artificial Intelligence

👥 B2C

Transport • Artificial Intelligence • B2C

Glydways is a company focused on transforming public transit through innovative and efficient mobility solutions. Their unique approach includes a seamless self-driving fleet operating on dedicated guideways, allowing for direct and congestion-free rides. Glydways aims to make transit accessible and financially sustainable, promoting the idea that access to mobility is essential for opportunity and community engagement.

📋 Description

• 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).

🏖️ Benefits

• Equal employment opportunities for all employees and applicants • Prohibits discrimination and harassment