San Francisco
Full-time - Senior Engineer
Social Networking & Media
Posted 3 weeks ago
Disclosed upon interview
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A leading global communications platform serves a highly engaged community of millions of daily active users, with a strong connection to the gaming community. The organization plays an important role in the future of gaming by helping people connect and have fun before, during, and after playing games.
The organization is seeking an experienced technical leader to strengthen its Data team and advance the analytical data infrastructure that supports trusted, self-service datasets across the business.
The role will work closely with Data Governance, Data Science, Product, Finance, and Engineering teams and will report to the Director of Data Engineering.
Key Responsibilities
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 strengthen data systems.
Navigate ambiguity and make sound technical decisions with incomplete information while balancing short-term delivery with long-term infrastructure investment.
Required Qualifications
7+ years of experience in data and software engineering with a strong focus on building curated, consumer-facing datasets.
7+ years of experience 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, with the ability to translate ambiguous business questions into concrete metric definitions.
Ability to explain complex technical implementations to audiences ranging from engineering peers to executive leadership.
Demonstrated track record of hands-on collaboration with Data Science, Finance, and Product teams.
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