Senior Analytics Engineer, Data Platform

The New York Times•New York, NY

2h•Onsite

About The Position

The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for. About the Role, Mission or Department Overview The Data Platform Mission aims to empower the organization to access and use data to answer important questions, power user experiences, and to make strategic decisions that drive value and impact across the organization. We are looking for Analytics Engineers that can help develop a new function within Data Platform that focuses on supporting our most critical data assets across The New York Times data domains. You will partner with many different teams and roles to develop data products, capabilities, and technologies. This role is based in our New York City office in Times Square. As a Senior Analytics Engineer, you'll work with teams across the organization to manage, support, and improve the quality of data across specific organizational domains that help to make data-driven decisions and experiences as efficient as possible. You will develop deep expertise within specific data domains, being a subject matter expert for the business and being an important partner across data initiatives. You will report to the Executive Director of Analytics Engineering.

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

Nice To Haves

Expertise with JSON, YAML, relational data modeling, and other data modeling languages and tools
Experience working with event-based and behavioral data and instrumentation

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
Establish data management frameworks that provide clear recommendations and requirements for data producers, while also working with data platform team to integrate into capabilities
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
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
Establish a process to implement, track, and ensure data quality frameworks are adhered to
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
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
Ensure the accuracy, completeness, consistency, and reliability of data within assigned domains
Collaborate with various teams to understand domain needs, prioritize initiatives, maintain data models, and oversee the implementation of data governance standards
Continuously improve data quality, identifies issues, and develops solutions to comply with regulatory requirements
Document data management standards and supports business data stewards
Identify and resolve data issues and risks within the domain
Monitor domain maturity index with KPIs of data governance, quality, integration, security, and analytics
Develop domain-specific documentation such as Data Use Cases and Data Flow Diagrams
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
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
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
Identify opportunities to streamline and automate reports, common business questions, etc.
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.