Data Architect

Responsibilities

• Define and own the data architecture strategy across all environments, platforms, and data domains.
• Establish and maintain architectural standards, patterns, and best practices for data ingestion, storage, modeling, and consumption.
• Design scalable, secure, and resilient data architectures on AWS, including data lake, lakehouse, warehouse, and serving layers.
• Define and champion a Medallion (bronze/silver/gold) architecture, establishing standards for raw, refined, and curated data layers and the promotion patterns between them.
• Lead the platform direction of Agency Bloc's cloud data warehouse/lakehouse, defining how each is used, where workloads run, and how cost and performance are managed.
• Establish data modeling standards (dimensional, Data Vault, and other patterns) that balance flexibility, performance, and maintainability.
• Define standards for batch and streaming pipelines, ETL/ELT frameworks, orchestration, and reuse patterns across teams.
• Lead tool and platform selection decisions (warehouse/lakehouse, ingestion, transformation, orchestration, catalog, BI), ensuring alignment with long‑term strategy.
• Conduct architecture reviews and provide guidance on complex or high‑impact data initiatives.
• Collaborate with engineering leadership to align data capabilities with product and business priorities.
• Define and own the data governance strategy, including data cataloging, lineage, classification, and ownership models.
• Establish data quality standards and frameworks, including validation, monitoring, and remediation practices.
• Partner with security and compliance teams to enforce secure‑by‑design principles for sensitive and regulated data, including access controls, encryption, masking, and PII handling (SOC 2 and relevant standards).
• Define data retention, archival, and lifecycle management standards.
• Partner with the Dev Ops Architect to define data pipeline observability standards, including monitoring, alerting, and SLAs/SLOs for freshness, completeness, and reliability, ensuring alerts surface high‑quality, actionable signals tied to business impact with minimal noise.
• Establish practices for cost monitoring and optimization across data platforms.
• Drive standardization and reduction of tool and pattern fragmentation across data teams.
• Mentor data engineers and senior data engineers, providing technical leadership and architectural guidance.
• Define the organization’s approach to enabling AI and ML workloads on the data platform, including feature data, governance, and adoption strategy.
• Establish patterns for delivering trusted, well‑governed data to AI/ML and analytics use cases.
• Evaluate emerging data and AI capabilities and incorporate them into the platform roadmap where they provide measurable value.

• Bachelor’s degree in Computer Science or equivalent experience preferred.
• 10+ years of experience in data engineering, data architecture, or analytics engineering.
• Proven experience designing and implementing large‑scale cloud data architectures (AWS preferred).
• Hands‑on expertise with Databricks and/or Snowflake in a production environment.
• Demonstrated experience designing and implementing Medallion (bronze/silver/gold) architectures.
• Strong experience with data modeling (dimensional, Data Vault, and related patterns) for analytical and operational use cases.
• Deep experience with ETL/ELT design, orchestration, and batch and streaming data pipelines at scale.
• Strong understanding of data governance, cataloging, lineage, and data quality frameworks.
• Expertise in data security and compliance, including access management, encryption, and PII handling (SOC 2 and similar frameworks).
• Strong background in SQL, automation, scripting, and modern data engineering practices (e.g., IaC and CI/CD for data).
• Experience evaluating and selecting data tools and platforms.
• Experience leading cross‑team technical initiatives and influencing engineering direction.
• Strong communication skills, with the ability to translate complex technical concepts to non‑technical stakeholders.
• Experience working in insurance, Insur Tech, or other regulated industries is a plus.
• Strategic thinking and long‑term planning.
• Systems design and architectural decision‑making.
• Cross‑team influence and alignment.
• Balancing standardization with team autonomy.
• Pragmatic execution and decision‑making.

• Bachelor’s degree in Computer Science
• SOC 2 compliance