Data Architect

Suffolk Construction•Boston, MA

44d

About The Position

Suffolk is scaling its Data and AI team to deliver real-time, predictive insights across the build lifecycle. We’re hiring a hands-on Data Architect to design, build, and operate the semantic layer, automated data quality controls (including AI-assisted checks), lineage, and access patterns that make our data discoverable, trusted, secure, and agentic AI ready. Reporting to the Director of Data Management, this individual will create reusable models/metrics, embed governance as code, and ensure every data product meets targets for reliability, availability, and semantic interoperability.

Requirements

5+ years in data architecture/engineering within a modern cloud stack; 2+ years owning a semantic/metrics layer at scale
Strong SQL/Python with Delta Lake, Unity Catalog, MLflow/Model Registry; experience with Delta Live Tables (or equivalent) for transformations
Proven track record standing up enterprise catalog/lineage and data quality automation
Working knowledge of access control patterns, data classification, and PII protections in analytical stacks; partners effectively with security teams
Excellent stakeholder skills, able to translate governance concepts to the broader teams

Responsibilities

Evolve lakehouse and platform architecture
Own the target architecture for Databricks on AWS (S3/EC2, Delta Lake, Unity Catalog, MLflow/Model Registry, Delta Live Tables) and the interfaces to Agentic AI stack/BI/IDE and downstream apps
Design ingestion and serving patterns, data contracts, and API/SQL access layers for internal consumers and agentic use cases
Plan platform evolution (governed multi-workspace layout, environment separation, lineage/observability) and drive high-impact upgrades and migrations with low downtime
Champion IaC & CI/CD (e.g., Terraform + GitHub Actions) for reproducible workspaces, catalogs, pipelines, and policies
Evolve enterprise data catalog, lineage & semantic layer
Deploy and maintain data catalog across Databricks
Build & evolve the semantic layer - design subject area models, define conformed dimensions and governed metrics, and expose them for BI, APIs, and AI agents
Extract business rules currently embedded in dashboards / SQL and refactor them into reusable transformations, tests, and metric definitions
Implement and maintain lineage, technical and business metadata, and documentation across Databricks Unity Catalog; ensure LLM-friendly metadata for RAG and AI agents
Lead scaling of the Master data (Project, Vendor, Budget, People etc.) and golden record rules
Implement automated data-quality & reliability controls
Embed rule-based and ML anomaly tests into pipelines and semantic layer
Define and monitor SLAs with incident playbooks
Drive continuous improvement to cut quality issues by 90 % year-over-year
Operationalize security & privacy by design for analytical data stack
Partner with CISO to maintain security of cloud infrastructure for analytics and AI
Develop and implement data classification and access framework
Own annual assessments and audits for analytical data stack
Ensure adherence to all applicable data regulations and policies
Build model & AI governance framework
Establish model registry, bias/drift monitoring, and audit trails for all predictive and GenAI models
Partner with Data Science to integrate governance checkpoints into pipelines
Drive adoption & data literacy
Champion “data-as-a-service” culture—making trusted data and insights the default for project teams