Data Platform & Operations Leader

Dotdash Meredith

New York (NY)

Hybrid

USD 190,000 - 205,000

Full time

14 days+

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Benefits offered by this job

401K match
Healthcare benefits
Paid time off

Job summary

People Inc. in New York, NY is seeking a Manager, Data Operations to lead the design, reliability, and day-to-day execution of core data pipelines and analytics infrastructure while directly managing a team of Data Engineers and Analytics Engineers.

You will set technical direction, prioritize work streams, and ensure alignment across Analytics, Product, and Technology. This hybrid NYC role allows remote work up to 3 days per week.

Qualifications

  • 7+ years building data pipelines with Python or similar
  • 5+ years advanced SQL in relational and distributed systems
  • Hands-on dbt for transformation and pipeline management
  • 2+ years leading or mentoring data/analytics engineers or delivering large data products
  • Strong leadership, communication, and documentation
  • Familiar with cloud platforms (BigQuery, Snowflake, AWS/GCP) and BI tools like Looker/Tableau

Responsibilities

  • Manage and mentor a team of data engineers building core data models and dashboards
  • Collaborate with stakeholders to gather requirements and deliver data solutions for reporting
  • Design and optimize well-documented data models enabling self-service analytics
  • Define best practices for code quality, docs, version control, and testing in analytics workflows
  • Lead or support ad-hoc analyses to uncover insights and drive strategy
  • Stay current with industry trends to improve data architecture and tooling

Skills

Python
SQL
Data pipelines
Leadership
Communication

Education

Bachelors in CS/Engineering

Tools

dbt
Looker
Tableau
BigQuery

Job description

Job Title

Manager, Data Operations

Job Description

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.

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/GCP.

  • 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.

It is the policy of People Inc. to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, the Company will provide reasonable accommodations for qualified individuals with disabilities.Accommodation requests can be made by emailing hr@people.inc.

The Company participates in the federal E-Verify program to confirm the identity and employment authorization of all newly hired employees. For further information about the E-Verify program, please click here:https://www.e-verify.gov/employees

Pay Range

Salary: New York: $190,000 - $205,000

The pay range above represents the anticipated low and high end of the pay range for this position and may change in the future. Actual pay may vary and may be above or below the range based on various factors including but not limited to work location, experience, and performance. The range listed is just one component of People Inc's total compensation package for employees. Other compensation may include annual bonuses, and short- and long-term incentives.In addition,People Inc. provides to employees (and their eligible family members) a variety of benefits, including medical, dental, vision, prescription drug coverage, unlimited paid time off (PTO), adoption or surrogate assistance, donation matching, tuition reimbursement, basic life insurance, basic accidental death & dismemberment, supplemental life insurance, supplemental accident insurance, commuter benefits, short term and long term disability, health savings and flexible spending accounts, family care benefits, a generous 401K savings plan with a company match program, 10-12 paid holidays annually, and generous paid parental leave (birthing and non-birthing parents), all of which may vary depending on the specific nature of your employment with People Inc. and your work location. We also offer voluntary benefits such as pet insurance, accident, critical and hospital indemnity health insurance coverage, life and disability insurance.

#NMG#
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