Glydways - Data Platform Engineering Lead

Remote4mo ago

Remote Staff WW Cloud Computing Data Analytics Data Engineer dbt SQL Airflow Docker Kubernetes

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).

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.