Staff Data Engineer

Dow Jones•New York, NY

1d•$160,000 - $200,000

About The Position

Dow Jones is hiring an individual-contributor Staff Engineer to lead Snowflake infrastructure across the enterprise. The Data Architecture & Platform Engineering team operates the data infrastructure behind Dow Jones products, analytics, and AI across B2B, B2C, and internal use cases. The role owns the Snowflake platform end to end, including account architecture and administration, security and access control, and DevOps capabilities that enable teams across business units to use Snowflake safely and effectively. The Staff Engineer will shape the platform’s AI capabilities by enabling efficient, cost-managed use of Cortex and other AI features, developing patterns for LLM-assisted workflows, and setting standards for building AI applications on governed data. The role combines hands-on work on high-stakes projects with platform-level decisions, standards-setting, and mentoring. It leads through technical influence, design reviews, working code, written proposals, and collaboration with security, compliance, finance, product, and engineering leaders.

Requirements

At least 7 years of experience in data engineering, platform engineering, or infrastructure roles, including experience at large or enterprise-scale companies.
Thought leadership on AI and strong opinions about making AI work effectively at scale on a data platform.
Deep, hands-on experience operating a production Snowflake account at scale, including administration, RBAC, security posture, cost, and performance.
Strong Terraform experience, using the Snowflake provider or an equivalent, and experience with CI/CD for data infrastructure.
Track record designing and operating data platforms that serve multiple teams, business units, or downstream systems.
Security fluency covering RBAC design, data masking, access policies, private connectivity, SSO, SCIM, and audit posture.
Experience with observability, monitoring, incident response, and on-call for data infrastructure.
Strong Python skills for platform tooling, automation, or service work.
Experience working in regulated or audited environments such as SOC 2, SOX, GDPR, or equivalent.
Bachelor’s degree in Computer Science, Engineering, or equivalent experience.
Ability to influence across teams and functions without formal authority, supported by strong written and verbal communication.

Nice To Haves

Experience with dbt, Airflow, or comparable orchestration and transformation tools.
Snowflake certifications, such as SnowPro Advanced: Administrator or Data Engineer.
Substantial Snowflake cost optimization or FinOps experience.
Experience with data governance, metadata, or lineage tools such as Collibra, Atlan, or Alation.
Cloud platform expertise, especially AWS, and platform operations at scale.
Experience with near-real-time or event-driven data processing.
Experience developing engineers through mentoring, design reviews, or communities of practice.

Responsibilities

Own the Snowflake footprint across Dow Jones, including accounts, warehouses, roles, databases, and the operating model.
Design and evolve RBAC, column- and row-level policies, masking, tagging, and data classification across business units.
Build and maintain Snowflake DevOps pipelines using 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 platform cost and performance through resource monitors, warehouse right-sizing, query analysis, credit budgeting, and FinOps reporting.
Design platform reliability through replication, failover, disaster recovery, incident response, and observability.
Explore and implement emerging AI tooling to accelerate modern data engineering practices.
Lead architecture and design reviews for major Snowflake initiatives.
Anticipate scalability, reliability, security, and cost issues before they arise.
Identify and reduce platform technical debt and complexity.
Debug difficult platform problems, lead during incidents, and determine root causes.
Mentor engineers at multiple levels, including senior and staff peers, through design guidance, code review, pairing, and documentation.
Contribute to engineering development practices, career frameworks, and communities of practice.
Communicate through design documents, wikis, and technical talks, tailoring communication for engineering, product, security, and executive audiences.