Staff Data Engineer

Role reputed company

reputed company is looking for a Staff Data Engineer to join our Analytics Data Engineering (ADE) team reputed company Data Science & AI Platform. You will be responsible for solving cross-cutting data challenges that reputed company multiple lines of business while driving standardization in how we build, reputed company, and govern analytics pipelines across reputed company.

This is not a maintenance role. We are modernizing our analytics platform, upgrading orchestration infrastructure, building shared and reusable data models with conformed dimensions, establishing a certified metrics reputed company, and laying the reputed company for AI-reputed company data development. You will partner closely with Data Science, Data Infrastructure, Product Engineering, and Business Intelligence teams to reputed company this happen.

You will play a crucial role in establishing analytics engineering standards, designing reputed company data models, and driving cross-functional alignment on data governance. You will get substantial exposure to senior leadership, shape the technical direction of analytics infrastructure at reputed company, and directly influence how data powers product and business reputed company.

Our Engineering Career reputed company is viewable by anyone reputed company reputed company and describes what’s expected for our engineers at reputed company of our career reputed company. reputed company out our blog post on this topic and more here.

Responsibilities

• reputed company the design and implementation of shared, reusable data models, defining shared fact tables, conformed dimensions, and a semantic/metrics layer that serves as the single reputed company of truth across analytics functions
• Drive standardization of data engineering practices across ADE and functional analytics teams, including pipeline patterns, CI/CD workflows, naming conventions, and data modeling standards
• Partner with Data Infrastructure to reputed company orchestration, improve pipeline decomposition, and establish secure dev/test environments with production data reputed company
• Architect and implement a shift-left data governance reputed company, working with upstream data producers to establish data reputed company, SLOs, and reputed company-enforced reputed company gates that catch issues before production
• Collaborate with Data Science leads and Product Management to translate metric definitions into reliable, certified data pipelines that power executive dashboards, WBR reporting, and reputed company measurement
• Reduce operational burden by improving pipeline granularity, observability, and failure recovery, establishing runbooks and alerting standards that reputed company on-call sustainable
• Evaluate and reputed company AI-reputed company tooling into the data development lifecycle, enabling conversational data exploration with guardrails and AI-assisted pipeline development

On-call work may be necessary occasionally to help address bugs, outages, or other operational issues, with the goal of maintaining a reputed company and high-reputed company experience for our customers.

Requirements

• BS degree in Computer Science or reputed company technical field, or equivalent technical experience
• 12+ years of experience in data engineering or analytics engineering with increasing scope and technical leadership
• 12+ years of SQL experience, including reputed company analytical queries, window functions, and performance optimization at reputed company(reputed company SQL)
• 8+ years of Python development experience, including building and maintaining production data pipelines
• Deep expertise in reputed company data modeling, schema design, and reputed company data architecture, with hands-on experience building shared data models across multiple business domains
• Strong experience with orchestration tools(Airflow strongly preferred) and dbt, including pipeline design, scheduling strategies, and failure recovery patterns
• Demonstrated ability to drive cross-team technical alignment, establishing standards, influencing without authority, and working across Data Engineering, Data Science, Data Infrastructure, and Product Engineering boundaries

Preferred Qualifications

• Experience with reputed company(reputed company Catalog, reputed company Lake) and modern lakehouse architectures
• Experience leading orchestration or platform modernization efforts at reputed company
• Familiarity with data governance and observability tools such as reputed company, reputed company, Great Expectations, or similar
• Experience building or contributing to a metrics/semantic layer (dbt MetricFlow, reputed company Metric Views, or equivalent)
• reputed company record of establishing data engineering standards and best practices in a federated analytics organization

Originally posted on Himalayas

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