Senior Manager, Data Engineering

OUTFRONT Media•New York, NY

2d•$180,000 - $210,000

About The Position

OUTFRONT Media is hiring a Senior Manager, Data Engineering to lead and grow its Data Engineering team within Data & Analytics. This is a hands-on player-coach role that combines team development and performance management with ownership of architecture, coding, technical reviews, and delivery of a modern data platform. The role also leads the team's adoption of AI-assisted engineering tools and the development of AI-enabled data solutions. The Senior Manager owns engineering standards, the team's backlog and delivery plan, and Agile practices. The role builds and maintains scalable data pipelines, models, and warehouse structures using AWS, Snowflake, dbt, and Fivetran, and provides the backend data foundation for dashboards, reporting, self-service analytics, and data science. It partners with analysts, product owners, and business stakeholders to define KPIs and scalable data products, while driving data quality, documentation, monitoring, incident response, reliability, and cost management. The position applies AI-assisted development tools such as Claude Code and Kiro, and AWS Amazon Bedrock and Snowflake Cortex capabilities, with safeguards for privacy, security, access, cost, and human review. A bachelor's degree in Computer Science or equivalent experience is preferred. The stated annual salary range is $180,000–$210,000.

Requirements

At least 8 years designing and implementing modern data warehouse and data engineering solutions.
Advanced SQL and Python skills and experience building robust ETL/ELT pipelines.
At least 3 years leading or managing data engineers while remaining hands-on in architecture and code.
Strong hands-on experience with AWS, Snowflake, dbt, and Fivetran, including Snowflake data modeling and dbt transformation workflows.
Experience running Agile delivery and applying product management practices such as roadmaps, prioritization, and outcome-based planning to data work.
Expert-level knowledge of Jira, Confluence, and the Atlassian suite, including boards, workflows, dashboards, and automation.
Hands-on fluency with AI-assisted coding tools such as Claude Code and Kiro, with examples of improving delivery speed 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, sufficient to guide data models and semantic layers for reporting.
Knowledge of modern data and analytics engineering practices, including CI/CD, testing, orchestration, infrastructure as code, and observability.
Knowledge of agentic and AI-assisted development practices, including prompt and context design, spec-driven development, and secure, maintainable review of AI-generated code.
Knowledge of generative AI on AWS and Snowflake, including Bedrock foundation models, knowledge bases, agents, and guardrails, and Cortex AI functions, Analyst, Search, and Cortex Code.
Knowledge of data modeling, semantic layer design, data governance, quality, security, and privacy.
Ability to develop and retain engineering talent, coach early-career engineers, and provide clear, candid feedback.
Ability to align technical and business stakeholders and explain complex concepts to non-technical audiences; product mindset, business sense, and judgment to assess AI's practical value.

Nice To Haves

Bachelor of Engineering in Computer Science or equivalent experience is preferred.
Experience with Tableau and/or Power BI is a plus.
Ad tech knowledge covering identity management, data privacy, audience targeting, cross-device graphs, ad serving, analytics, DSP, DMP, SSP, QA, and targeting.

Responsibilities

Hire, onboard, coach, and develop Data Engineers, particularly early-career engineers; manage performance and career growth.
Define and enforce engineering standards for pipelines, data modeling, testing, CI/CD, observability, and code review.
Own the data engineering backlog and delivery plan, prioritizing work with business and analytics partners around users and outcomes.
Lead Agile sprint planning, refinement, estimation, and retrospectives using Jira, Confluence, and the Atlassian ecosystem; use delivery metrics to improve predictability and stakeholder visibility.
Design and build scalable data pipelines, models, and warehouse structures with AWS, Snowflake, dbt, and Fivetran, and address difficult technical problems hands-on.
Own and optimize the backend data foundation for dashboards, reporting, self-service analytics in Sigma Computing, and data science, with attention to speed, reliability, cost, and maintainability.
Develop practical workflows and guardrails for Claude Code and Kiro, coach engineers in their use, and measure effects on productivity and quality.
Build AI-enabled data solutions using AWS Amazon Bedrock and Snowflake Cortex, with safeguards for privacy, security, access, cost, and human review.
Partner with analysts, product owners, and stakeholders to define KPIs and develop scalable data products.
Drive data quality, documentation, monitoring, incident response, and cost management across Snowflake and AWS.
Align technical and business stakeholders on priorities and trade-offs, communicate complex concepts to non-technical audiences, and apply product and business judgment to data and AI work.