Job Description:
Staff Engineer, Snowflake Platform
Dow Jones, Data Architecture & Platform Engineering
New York, United States | Job ID: TBD | Internal career level: Staff Engineer
Dow Jones is a global provider of news and business information, delivering content to consumers and organizations
around the world across multiple formats, including print, digital, mobile and live events.
About the team
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.
The role
This is an individual-contributor leadership role focused on Snowflake infrastructure at the Dow Jones enterprise
scale. You'll own the platform end to end: account architecture and administration, security and access control, and
the DevOps machinery that makes Snowflake safe and easy to use across dozens of teams and every business unit.
You will own the Snowflake platform's AI story: efficient, cost-managed access to Cortex and other AI features,
optimized patterns for LLM-assisted workflows, and standards that let engineers across DJ build with AI on top of
governed data.
You'll ship the hard parts yourself, set the standards other teams follow, and mentor the engineers who work in and
around Snowflake. You lead through influence: design reviews, working code, written arguments, and mentoring.
You'll partner with security, compliance, finance, product, and engineering leaders to turn DJ's data-platform goals
into infrastructure that holds up over time.
You'll split your time between hands-on Snowflake work on the highest-stakes projects; standards and platform-level
decisions; and mentoring engineers across levels.
What you'll do
• Own the Snowflake footprint across Dow Jones: accounts, warehouses, roles, databases, and the operating
model behind them.
• Design and evolve RBAC, column and row-level policies, masking, tagging, and data classification for
every business unit.
• Build and maintain the DevOps pipeline for Snowflake: Terraform, CI/CD for schema and object changes,
automated testing, and change management.
• Set and enforce standards for security, network policies, private connectivity, SSO, SCIM, and secrets
management.
• Optimize cost and performance: resource monitors, warehouse right-sizing, query analysis, credit
budgeting, and FinOps reporting.
• Design for reliability at DJ scale: replication, failover, disaster recovery, incident response, and
observability across the platform.
• Explore and implement emerging AI tooling to accelerate our modern data engineering practices.
• Lead architecture and design reviews for major Snowflake initiatives.
• Anticipate scalability, reliability, security, and cost problems before they land.
• Hunt technical debt in the platform to reduce complexity so downstream teams get more done with less.
• Debug the problems no one else can. Lead during incidents and get to root cause fast.
• Mentor engineers across levels, including senior and staff peers, through design guidance, code review,
pairing, and documentation.
• Contribute to how the org grows engineers: development practices, career frameworks, communities of
practice.
• Communicate through design docs, wiki, and tech talks; tailor the message for engineers, product, security,
and executives.
What we're looking for
• 7+ years in data engineering, platform engineering, or infrastructure roles, with time spent at large or
enterprise-scale companies.
• Thought-leader of AI and opinionated about how to make it work effectively at scale on a data platform.
Dow Jones invests heavily in AI and expects Staff engineers to shape how it lands.
• Deep, hands-on Snowflake experience running a production account at scale: administration,…