Manager, Data Operations

About The Position

The Manager, Data Operations leads the design, reliability, and day‑to‑day execution of the company’s core data pipelines and analytics infrastructure while directly managing a team of Data Engineers and Analytics Engineers. This role combines hands‑on technical leadership with people management accountability, ensuring that data systems are scalable, trusted, well‑documented, and aligned with business priorities. The role is responsible for setting technical direction, prioritizing team work‑streams, developing talent, and ensuring cross‑functional alignment across Analytics, Product, and Technology.

This is both a strategic leadership role and a hands‑on operational steward for the company’s data platform.

Hybrid NYC. This position is hybrid in‑office, with the ability to work remotely for up to 3 days per week.

• 30% Data Engineering & Pipeline Operations
  • Own the design, reliability, and scalability of ingestion, transformation, and storage pipelines
  • Ensure ELT/ETL processes run with high uptime and strong data quality
  • Guide orchestration, monitoring, and performance optimization
  • Reduce operational fragility by promoting shared patterns and automation
• 30% Analytics Engineering & Data Modeling
  • Oversee development and maintenance of clean, tested, well‑documented data models (e.g., dbt)
  • Define standards for modeling and semantic consistency
  • Ensure downstream BI and analytics consumers have trusted, well‑structured datasets
• 20% Governance, Quality & Trust
  • Establish clear metric definitions and semantic models
  • Partner with Governance and Security teams on lineage, metadata, and access controls
  • Reduce metric inconsistencies and reporting ambiguity
  • Ensure compliance with privacy and security standards
• 20% Business Partnership & Communication
  • Serve as a data advisor to Analytics, Product, and business leadership
  • Translate business priorities into technical roadmaps
  • Communicate complex technical concepts and trade‑offs clearly to technical and non‑technical audiences
  • Prioritize investments based on measurable business impact

• Manage and mentor a team of data engineers responsible for building and maintaining core data models, dashboards, and scalable data products.
• Collaborate with stakeholders to understand business needs, gather requirements, and deliver high‑quality data solutions that support reporting and decision‑making.
• Design, implement, and optimize performant, well‑documented data models that enable self‑service analytics and strategic initiatives.
• Define and champion engineering best practices around code quality, documentation, version control, and testing within analytics workflows.
• Lead or support ad‑hoc data analyses to uncover insights and drive business strategy.
• Stay up to date on industry trends and new technologies to continuously improve our data architecture, tooling, and processes.

• 7+ years of experience building and optimizing data pipelines using Python or similar programming languages.
• 5+ years of advanced SQL experience working with relational and distributed data systems (e.g., Hive, Big Query).
• Hands‑on experience with dbt for data transformation and pipeline management.
• 2+ years of experience leading or mentoring a team of data or analytics engineers, or owning end‑to‑end delivery of large‑scale data products.
• Strong leadership and talent‑development skills.
• Excellent communication across technical and business audiences.
• Strong prioritization, decision‑making, and documentation discipline.
• Familiarity with cloud data platforms such as Big Query, Snowflake, or AWS/GCP.
• Experience with data visualization tools such as Looker, Tableau, or similar is a plus.
• Bachelor’s degree in Computer Science, Engineering, or a…