Data Architect

Overview

Design, build, and manage a Databricks/AWS lakehouse, semantic layer, and data governance.

Key Responsibilities

• databricks architecture
• iac ci/cd
• data catalog
• model registry
• semantic layer
• lineage metadata

Tasks

-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 -Champion IaC & CI/CD (e.g., Terraform + GitHub Actions) for reproducible workspaces, catalogs, pipelines, and policies -Ensure adherence to all applicable data regulations and policies -Own annual assessments and audits for analytical data stack -Partner with CISO to maintain security of cloud infrastructure for analytics and AI -Embed rule-based and ML anomaly tests into pipelines and semantic layer -Lead scaling of the Master data (Project, Vendor, Budget, People etc.) and golden record rules -Develop and implement data classification and access framework -Deploy and maintain data catalog across Databricks -Champion “data-as-a-service” culture—making trusted data and insights the default for project teams -Establish model registry, bias/drift monitoring, and audit trails for all predictive and GenAI models -Plan platform evolution (governed multi-workspace layout, environment separation, lineage/observability) and drive high-impact upgrades and migrations with low downtime -Drive continuous improvement to cut quality issues by 90 % year-over-year -Partner with Data Science to integrate governance checkpoints into pipelines -Design ingestion and serving patterns, data contracts, and API/SQL access layers for internal consumers and agentic use cases -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 -Define and monitor SLAs (latency ≤ 15 min, uptime ≥ 99 %) with incident playbooks

Requirements

• sql
• python
• delta lake
• mlflow
• enterprise catalog
• stakeholder

What You Bring

-Working knowledge of access control patterns, data classification, and PII protections in analytical stacks; partners effectively with security teams -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 -Excellent stakeholder skills, able to translate governance concepts to the broader teams

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About Suffolk Construction

-From its Boston headquarters, they expanded through strategic acquisitions in healthcare and regional offices across the US. -Their portfolio spans iconic projects like Wynn Everett casino, GE’s Boston headquarters, major airports, and mixed-use towers. -They offer full-spectrum services: pre-construction, construction management, general contracting, and design-build. -They operate Centers of Excellence across sectors such as aviation, mission-critical, education, healthcare, and hospitality. -Their approach combines cutting-edge technologies like AI, VR, and virtual design with collaborative, people-focused execution. -Notable innovations include VR groundbreaking ceremonies and AI-driven risk modeling on complex builds. -Projects range from large-scale casinos and airport terminals to universities, residential towers, and mission-critical facilities. -Despite its scale, they maintain a reputation for a regimented culture and a meritocratic, performance-driven ethos.

Sector Specialisms