Staff Systems Engineer, Digital

What you'll do

• Define and own the enterprise data architecture strategy across operational, analytical, and AI/ML workloads.
• Design and govern data models, data contracts, and canonical schemas for product and platform teams.
• Evaluate and standardize data platform tooling including data lakes, warehouses, and streaming layers.
• Own data governance frameworks including classification, lineage, quality standards, and HIPAA/CCPA compliance.
• Design data architectures that support AI/ML model training, feature engineering, and inference pipelines.
• Establish data quality frameworks including schema validation, freshness SLAs, and anomaly detection.
• Define observability standards for data pipelines including alerting, lineage tracking, and incident response.
• Act as a technical advisor and escalation point for complex data architecture decisions across teams.

What we're looking for

• 7+ years of experience in data engineering, data architecture, or related roles.
• 5+ years of hands-on experience with cloud-native data platforms like GCP (BigQuery, Dataflow, Pub/Sub) or Azure Synapse.
• 5+ years of experience with data governance, compliance, and regulatory requirements.
• Bachelor's degree or equivalent experience (HS diploma + 4 years relevant experience).
• Proven track record of building and governing enterprise-scale data platforms across multiple product teams (preferred).
• Strong communication skills to translate complex data architecture decisions for technical and non-technical stakeholders (preferred).
• Deep expertise in relational and non-relational data modeling, including dimensional modeling, Data Vault, or event-sourced patterns (preferred).
• Strong command of SQL and at least one data pipeline language such as Python, Scala, or Spark (preferred).