Senior Manager, Data Engineering
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Role details
Tech stack
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Job description
- Build and grow the team: Hire, onboard, coach and develop Data Engineers, with a focus on early-career talent. Youβll also own performance management and career growth.
- Set the bar: Define and enforce engineering standards for pipelines, data modeling, testing, CI/CD, observability and code review.
- Treat data as a product: Own the backlog and delivery plan, and prioritize with business and analytics partners around clear users and outcomes.
- Run strong Agile delivery: Lead sprint planning, refinement, estimation and retros in Jira, Confluence and the Atlassian ecosystem. Use delivery metrics to improve predictability and give stakeholders clear visibility.
- Stay hands-on: Design and build scalable pipelines, models and warehouse structures with AWS, Snowflake, dbt and Fivetran, and take on the hardest technical problems yourself.
- Power the business: Own the backend data foundation behind dashboards, reporting, self-service analytics in Sigma Computing, and data science, and optimize it for speed, reliability, cost and maintainability.
- Lead the AI shift in engineering: Build practical workflows and guardrails for Claude Code and Kiro, coach engineers, and measure the impact on productivity and quality.
- Ship AI-enabled data solutions: Build on AWS Amazon Bedrock and Snowflake Cortex (AI functions, Cortex Analyst, Cortex Search, Cortex Code) with strong guardrails for privacy, security, access, cost and human review.
- Partner across the business: Work with analysts, product owners and stakeholders to define KPIs and turn them into scalable data products.
- Keep it reliable: Drive data quality, documentation, monitoring, incident response and cost management across Snowflake and AWS., * Modern data and analytics engineering: CI/CD, testing, orchestration, infrastructure as code and observability
- Agentic and AI-assisted development: prompt and context design, spec-driven development, and review practices that keep AI-generated code secure and maintainable
- Generative AI on AWS and Snowflake: Bedrock (foundation models, knowledge bases, agents, guardrails) and Cortex (AI functions, Analyst, Search, Cortex Code)
- Data modeling, semantic layer design, data governance, quality, security and privacy
- Ad tech knowledge: identity management, data privacy, audience targeting, cross-device graphs, ad serving, analytics, DSP, DMP, SSP, QA and targeting
How You Lead
- You develop and keep strong engineering talent, coach early-career engineers, and give clear, candid feedback.
- You align technical and business stakeholders on priorities and trade-offs.
- You can explain complex concepts to non-technical audiences.
- You have a product mindset, business sense, and the judgment to separate AI hype from real value.
Requirements
- 8+ years designing and implementing modern data warehouse and data engineering solutions, with advanced SQL, Python and robust ETL/ELT pipelines
- 3+ years leading or managing data engineers while staying hands-on in architecture and code
- *Strong hands-on experience with AWS, Snowflake, dbt and Fivetran, including data modeling in Snowflake and transformation workflows in dbt
- A track record of running Agile delivery and applying product management practices (roadmaps, prioritization, outcome-based planning) to data work
- Expert-level knowledge of Jira, Confluence and the Atlassian suite, including boards, workflows, dashboards and automation
- Demonstrated, hands-on fluency with AI-assisted coding tools such as Claude Code and Kiro, with real examples of delivering faster without sacrificing quality or security
- Working experience with AWS Amazon Bedrock and Snowflake Cortex (including Cortex Code) to build or enable generative AI solutions
- Familiarity with BI and self-service platforms, ideally Sigma Computing (Tableau and/or Power BI a plus), enough to guide data models and semantic layers that support reporting, Bachelor of Engineering in Computer Science or equivalent experience preferred.
Benefits & conditions
The salary range for this role is $180,000 - $210,000 annually. Compensation is determined during our interview process by assessing a candidateβs experience and skills relative to internal peers and market benchmarks evaluated for the scope and responsibilities of the position, and collective bargaining agreement terms. Please note that the foregoing compensation information is a good-faith assessment associated with this position only and is provided pursuant to the New York Salary Transparency Law.
About the company
The best ideas in advertising donβt only live on a screen. They live on the street, in the subway, along the freeway and in the moments people actually notice. At OUTFRONT Media, we call that βIn Real Lifeβ (IRL) media, and weβre looking for a leader to bring it to the most entrepreneurial corner of the agency world.
Weβre hiring a Senior Manager, Data Engineering to lead and grow our Data Engineering team within Data & Analytics. This is a true player-coach role. Youβll develop a team of engineers, including early-career talent, and still get your hands dirty in architecture, code and technical reviews. Youβll also set the pace for AI-assisted engineering across the team, using tools like Claude Code, Kiro, AWS Amazon Bedrock and Snowflake Cortex AI.
If you want to build a strong team and a modern, AI-powered data platform at the same time, this role is for you.
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