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DotDash Meredith

Multi-brand digital and print publisher

Manager, Data Operations

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeNew York, NY, USA

About the Job

Requirements

  • At least 7 years of experience building and optimizing data pipelines using Python or similar programming languages.
  • At least 5 years of advanced SQL experience working with relational and distributed data systems such as Hive or BigQuery.
  • Hands-on experience with dbt for data transformation and pipeline management.
  • At least 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.
  • A bachelor's degree in Computer Science, Engineering, or a related field.

Responsibilities

  • Lead the design, reliability, and day-to-day execution of core data pipelines and analytics infrastructure while managing a team of Data Engineers and Analytics Engineers.
  • Set technical direction, prioritize team workstreams, develop talent, and ensure cross-functional alignment across Analytics, Product, and Technology.
  • 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.
  • Promote shared patterns and automation to reduce operational fragility.
  • Oversee development and maintenance of clean, tested, and well-documented data models, including dbt models.
  • Define standards for modeling and semantic consistency.
  • Ensure downstream business intelligence and analytics consumers have trusted, well-structured datasets.
  • 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.
  • Advise Analytics, Product, and business leadership on data matters.
  • Translate business priorities into technical roadmaps.
  • Communicate technical concepts and trade-offs 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 data solutions supporting reporting and decision-making.
  • Design, implement, and optimize performant, well-documented data models that enable self-service analytics and strategic initiatives.
  • Define and promote engineering best practices for code quality, documentation, version control, and testing within analytics workflows.
  • Lead or support ad hoc data analyses to uncover insights and inform business strategy.
  • Track industry trends and new technologies to improve data architecture, tooling, and processes.

Desired Qualifications

  • Experience with data visualization tools such as Looker, Tableau, or similar.

About the Company

DotDash Meredith

Multi-brand digital and print publisher

DotDash Meredith is a leading digital and print publisher with brands like PEOPLE, Better Homes & Gardens, Allrecipes, Investopedia, and Verywell. It creates and distributes content across websites, magazines, and social media, covering health, finance, food, lifestyle, and beauty. Revenue comes from advertising, subscriptions, and partnerships, including co-branded content and joint marketing. The company differentiates itself through its large portfolio of trusted brands, broad cross-platform reach, and multiple revenue streams aimed at attracting readers, subscribers, and advertisers; its goal is to maintain leadership in media and publishing by delivering high-quality content.

Company size
1,001-5,000
Company stage
Debt Financing
Total funding
$515M
Headquarters
New York City, New York
Founded
1902

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