USAStaff Data Engineer - Data Infrastructure
2 нед. назад
USALead
data governancedata infrastructuredata modeling
Technical leader responsible for defining strategy and architecture for analytics data infrastructure and governance programs.
Обязанности
- Define technical strategy and architectural direction for analytics data infrastructure, building and maintaining enterprise-scale curated datasets and data models
- Own the design and implementation of data governance programs end to end, by partnering with stakeholders and translating policy requirements into flexible and configurable infrastructure in partnership with Data Platform Engineering.
- Design and build sophisticated data abstractions 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
Будет плюсом
- Passion for 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 $279,000 to $310,000 + 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.
- Why ? plays a uniquely important role in the future of gaming. We're a multiplatform, multigenerational and multiplayer platform that helps people deepen their friendships around games and shared interests, and helps developers build and grow their businesses. We believe games give us a way to have fun with our favorite people, whether listening to music together or grinding in competitive matches for diamond rank. Join us in our mission! Your future is just a click away!
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Другое
- has a highly engaged community of millions of daily active users who use the platform for many different reasons, but there’s one thing that nearly everyone does: play video games. plays a uniquely important role in the future of gaming, and we are focused on making it easier and more fun for people to hang out before, during, and after playing games.
- is looking for a seasoned technical leader to join our Data team as a Staff Data Engineer. You will drive technical vision and strategy for our analytical data infrastructure which facilitates the transformation and semantic layer that powers clean, tested, well-documented datasets that the company can trust and self-serve from. The data your team builds 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 Governance, Data Science, Product, Finance, and Engineering teams. This role reports to the Director of Data Engineering.
- 7+ years of experience in data and software engineering with a strong focus on building curated, consumer-facing datasets
- 7+ years of experience in designing, developing, and maintaining data infrastructure used by data teams at scale.
- 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
- 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