J.D. Power is clear about what we do to ensure our success into the future. We unite industry leading data and insights with world-class technology to solve our clients’ toughest challenges. We POWER Our Customer's Success We are Innovative, Collaborative and Grounded in Data We Make Things Easy We Get It Done We Start with Trust & Prove it Everyday
Senior Data Platform Engineer
Location
United States + 1 moreAll locations: United States | Canada
Posted
4 days ago
Salary
$120K - $150K / year
Seniority
Senior
Job Description
Senior Data Platform Engineer
J.D. Power
Role Description Own the hands-on engineering of JD Power's Snowflake data platform. Responsible for translating the Platform Lead's architecture and governance direction into a production-grade, automated, and observable Snowflake environment that supports analytics, product, and AI/ML workloads across the enterprise. The Scope & Ownership You Will Have in This Role: - Owns Snowflake account, warehouse, and object architecture. - Infrastructure-as-Code repository and CI/CD for all Snowflake changes. - RBAC implementation, security controls, and identity integration. - Ingestion and integration patterns (Snowpipe, Streams/Tasks, managed connectors). - Platform observability, cost monitoring, and performance tuning. - Documentation, runbooks, and onboarding patterns for platform consumers. Does not own: - Governance policy and strategy (owned by the Platform Lead). - Business data modeling and semantic layer (owned by Analytics Engineering). - Source system data quality at point of capture (owned by upstream teams). What You’ll Be Doing in This Role: - Design and evolve Snowflake account, warehouse, and object architecture. - Implement and maintain all Snowflake objects, roles, and policies in Terraform. - Operate database CI/CD using Schemachange, Liquibase, or equivalent. - Tune performance: clustering, search optimization, materialized views, query profiling. - Build and maintain the functional/access role hierarchy enforcing least privilege. - Implement masking policies, row access policies, object tagging, and network policies. - Integrate Snowflake with IdP for SSO/SCIM; manage service accounts and key rotation. - Partner with InfoSec, Privacy, and Compliance on audit readiness and control attestation. - Operate Snowpipe, Snowpipe Streaming, Streams/Tasks, and Kafka Connector pipelines. - Manage Fivetran/Airbyte (or equivalent) connector deployments and reliability. - Implement Iceberg / external tables where lakehouse interoperability is required. - Integrate with orchestration (Airflow / dbt Cloud) and observability tooling. - Define and meet SLOs for platform reliability, freshness, and cost. - Build dashboards and alerting; lead incident response for platform issues. - Document architecture decisions, patterns, and runbooks. - Enable Analytics Engineering, Product Engineering, and Data Science consumers. Qualifications - 5+ years of professional data platform, data engineering, or data infrastructure experience. - 3+ years of hands-on Snowflake experience at production scale (not pilot/POC). - Demonstrated expertise in Snowflake RBAC design, warehouse sizing and cost governance, performance tuning, and security features. - Strong SQL — able to read and optimize a query profile. - Python for tooling, automation, and pipelines. - Production IaC experience — Terraform required; Snowflake provider strongly preferred. - Database CI/CD using Schemachange, Liquibase, dbt, or equivalent change-management tooling. - Cloud fluency in AWS — networking, IAM, storage, and Snowflake integration points. - Ingestion experience with Snowpipe, Streams/Tasks, Kafka, and/or Fivetran/Airbyte. - Communication — able to author decision records and runbooks; able to influence without authority. Requirements - SnowPro Advanced certification (Architect, Data Engineer, or Administrator). - Hands-on dbt and modern Analytics Engineering experience. - Experience with Snowflake Horizon Catalog, Polaris, Collibra, or Alation. - Streaming and CDC: Kafka, Debezium, Snowpipe Streaming, Dynamic Tables. - Iceberg / lakehouse architecture. - Data observability tooling (Monte Carlo, Bigeye, Datadog). - Automotive, financial services, insurance, or regulated consumer-data experience. - AI/ML workloads on Snowflake (Cortex, Snowpark, feature stores). Benefits - This position has a starting salary range of $120K -$150K USD/$110K -$120K CAD per year. - An employee’s pay within the range is determined by a number of factors, including relevant skills, education, qualifications, experience, performance, business or organizational needs, and geographic location.
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