Full-Time

Senior Analytics Engineer

Data Platform

The New York Times

The New York Times

10,001+ employees

Subscription-based digital and print journalism

Compensation Overview

$124k - $135k/yr

New York, NY, USA

In Person

Category
Data & Analytics (1)
Required Skills
Python
Airflow
Data Science
Git
SQL
ETL
AWS
Data Governance
Google Cloud Platform
Requirements
  • 5+ years in business intelligence, product analytics, data management, or data governance
  • Proficiency in Python, SQL, and data APIs to work with large, complex datasets across multiple business domains
  • Understand, and prototype scripts to support data pipelines, business rules, quality checks, and general data lifecycle activities
  • Expert with DBT, Airflow, and other ETL/ELT orchestrators
  • Expert with version control (Github, code review)
  • Proficiency with GCP, AWS, or other big data environments
  • Familiarity with business intelligence tools and developing dashboards
  • Knowledge of industry-leading data governance, quality, and data management practices and tools
Responsibilities
  • Data Platform Evangelist: Provide frameworks, training, and guidance to individuals across the organization to utilize data platform capabilities or to submit well-defined data needs and requests
  • Data Platform Evangelist: Establish data management frameworks that provide clear recommendations and requirements for data producers, while also working with data platform team to integrate into capabilities
  • Data Platform Evangelist: Embed and work closely with data platform teams to build out governance into core capabilities
  • Data Quality: Create and maintain data quality frameworks, definitions, and metrics that are consistently applied across data domains, products, and key data assets
  • Data Quality: Define and test business logic to identify and surface domain-specific quality measures in conjunction with other data teams, that can be passed to data platform teams to implement once validated
  • Data Quality: Establish a process to implement, track, and ensure data quality frameworks are adhered to
  • Data Quality: Proactively monitor, surface, triage and track key data issues for data products and systems that provide visibility for data producers and data consumers to react accordingly, including the development of enterprise dashboards
  • Data Quality: Partner with data engineering teams to test and build out capabilities that promote quality, including data lineage, testing frameworks, writing quality checks, etc.
  • Domain Support: Maintain, update, and evolve our enterprise data and metrics catalogs
  • Domain Support: Ensure the accuracy, completeness, consistency, and reliability of data within assigned domains
  • Domain Support: Collaborate with various teams to understand domain needs, prioritize initiatives, maintain data models, and oversee the implementation of data governance standards
  • Domain Support: Continuously improve data quality, identifies issues, and develops solutions to comply with regulatory requirements
  • Domain Support: Document data management standards and supports business data stewards
  • Domain Support: Identify and resolve data issues and risks within the domain
  • Domain Support: Monitor domain maturity index with KPIs of data governance, quality, integration, security, and analytics
  • Domain Support: Develop domain-specific documentation such as Data Use Cases and Data Flow Diagrams
  • Domain Support: Provide support and training to the business regarding data governance and modeling
  • Analytics Enablement: Work closely with data platform to pilot, test, and build out user-friendly ways to consume data products
  • Analytics Enablement: Collaborate with business stakeholders, Data and Insights teams, and Data Platform product managers to gather requirements and translate into effective, user-friendly dashboards, reports, datasets, or artifacts
  • Analytics Enablement: Design and launch enterprise-wide dashboards and data visualization tools to track key enterprise and business metrics, for internal clients, stakeholders, and the executive team
  • Analytics Enablement: Identify opportunities to streamline and automate reports, common business questions, etc.
  • Analytics Enablement: Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.
Desired Qualifications
  • Expertise with JSON, YAML, relational data modeling, and other data modeling languages and tools
  • Experience working with event-based and behavioral data and instrumentation

The New York Times provides digital and print news across politics, business, technology, culture, and more for a global audience. It earns revenue from recurring subscriptions for digital and print editions and from online advertising, including sponsored content. It enhances value with subscriber services like NYT Cooking and other offerings, delivered through a digital platform, newsletters, and mobile apps. Its goal is to deliver trusted information and insightful analysis at scale while expanding its digital reach and subscriber value.

Company Size

10,001+

Company Stage

IPO

Headquarters

New York City, New York

Founded

1850

Simplify Jobs

Simplify's Take

What believers are saying

  • Berkshire Hathaway's $350 million stake validates NYT's value in 2025.
  • Lawsuit against OpenAI creates AI licensing revenue opportunities.
  • Serial Productions partnership boosts investigative journalism reach.

What critics are saying

  • OpenAI countersues NYT, escalating costs within 3-6 months.
  • Substack poaches ex-NYT writers, eroding subscribers in 12-24 months.
  • Berkshire pressures cost cuts, forcing NYT Cooking divestiture in 18-24 months.

What makes The New York Times unique

  • NYT Cooking offers specialized recipes, attracting dedicated subscribers.
  • 98 Pulitzer Prizes distinguish NYT as top journalistic honor winner.
  • 10 million paid digital subscriptions lead global news platforms.

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