Data Engineer, Analytics Data Products New York, NY

New York Times; California (MO); On-site; USD 110,000 - 130,000; Full time

Benefits offered by this job

Annual bonus

Company-matching 401(k) plan

Paid parental leave

Tuition reimbursement

Job summary

A leading news organization is seeking a Data Engineer to develop and manage data pipelines in a dynamic, remote-friendly setting. The ideal candidate has over two years of experience, strong SQL and Python skills, and familiarity with cloud platforms like GCP and AWS. You will be responsible for creating scalable data models, optimizing performance, and ensuring data quality in an evolving analytics environment. This role offers competitive pay and a comprehensive benefits package.

Qualifications

• 2+ years of hands-on experience in Data Engineering, Data Warehousing, or similar roles.
• Experience with complex production-level data modeling.
• Familiarity with cloud data warehouse solutions.

Responsibilities

• Design and implement ELT/ETL pipelines for data layers.
• Develop data transformations using dbt.
• Collaborate with teams to define and model data requirements.

Skills

SQL proficiency

Python for scripting

Data modeling

Cloud services familiarity

Education

Bachelor's degree or equivalent

Tools

PySpark

Airflow

Terraform

Job description

Office: New York, NY
Department: Technology — Software Engineering

Job Description

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:

We are part of a New York-based technology organization with a remote-friendly workplace that includes engineers around the world. We value transparency and openness, learning, community, and continuous improvement. Check out the Times Open blog , which is written by engineers and other technical team members, and follow @nytdevs on Twitter to see what we’re up to.

Responsibilities

Design, model, and implement complex ELT/ETL pipelines for the cleansed and curated data layers in the medallion architecture, taking full ownership of the data product's structure, partitioning, documentation, and performance characteristics.

Develop advanced data transformations using dbt (data build tool) for relational data modeling and PySpark for large-scale data processing within the Lakehouse, ensuring outputs meet strict Service Level Agreements and quality standards.

Collaborate across teams to define requirements and translate them into robust and scalable data models suitable for analytic consumption.

Manage the physical data storage across both GCP and AWS, selecting optimal file formats and designing efficient partitioning and clustering strategies.

Administer and tune Spark compute resources (e.g., Dataproc, EMR, or managed services) to optimize job execution time and cost.

Own core components of our centralized analytics environment, specifically focused on Hex, integrations, and the methods of data exposure and access controls; and support data activation strategies, ensuring seamless data consumption by analytic tools.

Optimize user queries and access patterns to maintain platform performance and cost efficiency.

Implement centralized data quality checks and observability mechanisms within the data pipeline to proactively identify and resolve data issues.

Contribute to the implementation of metadata management, data lineage, and role-based access control (RBAC) initiatives across the Lakehouse environment.

• Demonstrate support and understanding of ourvalue of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications

2+ years of hands‑on experience in a Data Engineering, Data Warehousing, Analytics Engineering or equivalent role

Proficiency in SQL and experience with complex, production‑level data modeling (dimensional modeling, Kimball, OBT, or Data Vault)

Demonstrated experience designing, developing, and deploying end‑to‑end data products through the full Software Development Lifecycle

Experience with a Cloud Data Warehouse, like BigQuery

Proficiency in Python for scripting and data manipulation, including knowledge of PySpark or other Spark APIs

Familiarity with cloud services and data storage components in at least one major cloud provider (GCP or AWS)

Experience with workflow orchestration tools (e.g., Airflow, Cloud Composer, or Prefect) and version control systems (Git)

Preferred Qualifications

Experience operating in a dual‑cloud environment (GCP/AWS)

Experience with Infrastructure‑as‑Code (IaC) tools like Terraform

Experience with advanced Lakehouse file formats like Iceberg or Delta Lake

Familiarity with experimentation or A/B testing platforms and the data required to support them

Experience in data product quality standards through integration advanced testing, quality checks, and monitoring into the CI/CD pipeline

REQ-019489

#LI-hybrid

The annual base pay range for this role is between:

$110,000 — $130,000 USD

For roles in the U.S., dependent on your role, you may be eligible for variable pay, such as an annual bonus and restricted stock. Benefits may include medical, dental and vision benefits, Flexible Spending Accounts (F.S.A.s), a company‑matching 401(k) plan, paid vacation, paid sick days, paid parental leave, tuition reimbursement and professional development programs.

For roles outside of the U.S., information on benefits will be provided during the interview process.

The New York Times Company is committed to being the world’s best source of independent, reliable and quality journalism. To do so, we embrace a diverse workforce that has a broad range of backgrounds and experiences across our ranks, at all levels of the organization. We encourage people from all backgrounds to apply.

We are an Equal Opportunity Employer and do not discriminate on the basis of an individual's sex, age, race, color, creed, national origin, alienage, religion, marital status, pregnancy, sexual orientation or affectional preference, gender identity and expression, disability, genetic trait or predisposition, carrier status, citizenship, veteran or military status and other personal characteristics protected by law. All applications will receive consideration for employment without regard to legally protected characteristics. The U.S. Equal Employment Opportunity Commission (EEOC)’s Know Your Rights Poster is available here .

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