Staff Data Engineer, Analytics

the company is looking for a seasoned technical leader to join our Data team as a Staff Data Engineer, Analytics. You will drive technical vision and strategy for our analytical data infrastructure, owning the transformation and semantic layer that powers clean, tested, well-documented datasets that the company can trust and self-serve from. The data you build won't just inform internal decisions, it will underpin the metrics we share with investors, partners, and the public, requiring exceptional rigor, auditability, and precision. This role works closely with Data Science, Product, Finance, and Engineering teams. What You'll Be Doing Define technical strategy and architectural direction for analytics data infrastructure, building and maintaining enterprise-scale curated datasets and data models Own metric definitions end to end, from partnering with stakeholders to define what we measure, to designing and implementing data model in production, to surfacing metrics and dimensions in dashboards and reports Design and build sophisticated data models and analytical frameworks using SQL, Python, and modern data stack technologies Develop data quality frameworks, monitoring, anomaly detection, and alerting at massive scale, with governance, lineage tracking, and change management rigor appropriate for externally reported numbers Drive adoption of consistent data modeling patterns, naming conventions, documentation norms, and metric governance standards across the data organization Lead cross-functional technical initiatives across product verticals and mentor engineers to accelerate delivery and harden data systems Navigate ambiguity and make sound technical decisions with incomplete information, balancing short-term delivery with long-term infrastructure investment What you should have 7+ years of experience in analytics or data engineering with a strong focus on building curated, consumer-facing datasets 7+ years of experience in designing, developing, and maintaining robust data models from structured and unstructured sources Expert-level SQL and strong Python skills, with solid fundamentals in version control and CI/CD Proven experience implementing data quality audits, monitoring systems, and automated remediation for massive datasets Experience building and owning executive-level dashboards and reports using BI tools (e.g., Looker, Tableau, or similar) Strong business acumen and communication skills, comfortable translating ambiguous business questions into concrete metric definitions and explaining complex implementations to audiences from engineering peers to executive leadership Track record of hands-on collaboration with Data Science, Finance, and Product teams Bonus Points Passion for the company or online communities Experience building or contributing to a semantic layer or metrics store Experience with modern analytics and data engineering tools and workflows (dbt, BigQuery, or similar) Experience defining and governing metric standards across a data organization Experience with reporting infrastructure subject to external audit or SOX compliance The US base salary range for this full-time position is $248,000 to $279,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits. the company is committed to inclusion and providing reasonable accommodations during the interview process. We want you to feel set up for success, so if you are in need of reasonable accommodations, please let your recruiter know. #J-18808-Ljbffr United States Digital Space LLC