Software Engineer - Data Architecture & Platform Engineering

Dow Jones & Company•New York City, NY

11h•Hybrid

About The Position

Our Technology team drives the evolution of our Technology, Engineering, Data, Product and User Experience functions. With a keen focus on delivering cutting-edge solutions, we shape the digital landscape for our customers, readers and users. From revolutionizing visuals to optimizing tools and harnessing the power of data, mobile, video and social platforms, our team is committed to providing a seamless and immersive experience across all touchpoints. Collaborating closely with our newsrooms and strategic partners, we spearhead the development of groundbreaking products and technologies. The Data Architecture & Platform Engineering team runs the data infrastructure behind Dow Jones products, analytics, and AI across B2B, B2C, and internal use cases. We own the Snowflake footprint which serves as the foundation of all DJ structured data, the surrounding platforms and patterns, and the governance framework. We build for scale, reliability, security, and cost efficiency. In this role, you will have an important role in supporting our newly branded Dow Jones Energy products and work closely with our US-based Energy business and technical stakeholders. You will work on a modern data platform built on Snowflake, dbt, Airflow, and Python. You'll own small-to-medium features end-to-end, from technical design through implementation, testing, deployment, and operational support. You also will use AI coding assistants in your everyday work, and pitch in when the team experiments with LLM-assisted approaches to data engineering: query generation, data profiling, documentation, and pipeline debugging. You'll partner with analytics, product, and other engineering teams to ship data solutions people actually use. You will report to the Director - Data Architecture & Platform Engineering.

Requirements

1-2 years’ relevant experience in data engineering, software engineering, or database development
Excitement about AI landscape and are curious how it's changing the shape of data engineering
Strong SQL, ideally within a cloud warehouse (Snowflake preferred; BigQuery or Redshift acceptable)
Working knowledge and experience with using Python for data processing, automation, or scripting
Exposure to modern data tooling: Airflow, dbt, or comparable orchestration and transformation frameworks
Familiarity with Git and a mainstream CI/CD workflow
Degree in Computer Science or related discipline -OR- equivalent work experience

Nice To Haves

Tableau or another mainstream BI tool
PowerShell or similar scripting
Data governance, lineage, privacy, or access-control experience
Cloud platform experience (AWS, GCP, or Azure); Terraform or another infrastructure-as-code tool; APIs
Postgres or another traditional RDBMS

Responsibilities

Build and maintain ELT pipelines in dbt and Snowflake, orchestrated with Airflow
Write tested SQL and Python for ingestion, transformation, validation, and delivery
Design data models that integrate multiple sources and hold up under downstream use
Contribute to CI/CD, testing frameworks, observability, and data-quality checks
Monitor pipeline health - investigate issues, propose fixes, and escalate when stuck
Take part in code review, technical design, on-call rotation, and production support
Translate requirements from analysts, product managers, and stakeholders into working data solutions