Manager, Data Operations

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.

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

About The Position's Contributions:

Accountabilities, Actions, and Expected Measurable Results

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

What You'll Do:
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.

What You Bring:
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, BigQuery).
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 BigQuery, Snowflake, or AWS/Google Cloud Platform.
Experience with data visualization tools such as Looker, Tableau, or similar is a plus.
Bachelor's degree in Computer Science, Engineering, or a related field.