Senior Data & Platform Engineer

GID is a privately-held, vertically-integrated real estate company that develops multifamily and mixed-use projects across the United States. The Senior Data & Platform Engineer is responsible for the technical execution and evolution of GID's enterprise data platform, ensuring it is scalable, secure, and ready to power analytics and internal applications.

Responsibilities:

• Own design architecture, reliability, and performance of the enterprise data platform—including ingestion, storage, processing, orchestration, and consumption layers
• Implement and maintain modern data stack components (e.g., Snowflake, DBT, orchestration frameworks, metadata tools, quality frameworks)
• Ensure platform scalability, availability, security posture, and cost efficiency
• Build and maintain analytics‑ready and AI‑ready data pipelines, transformation models, semantic layers, and shared data services
• Develop and execute a unified and forward-looking vision for data products and engineering
• Set foundation for AI use cases with implementation of semantic layer, context graphs, vector DBs, and stay current with the latest best practices
• Design and implement reusable data assets, domain models, and standardized transformation patterns
• Establish and enforce standards for data quality, data contracts, observability, lineage, and metadata management
• Implement access controls, RBAC, PII protection, and compliance with privacy regulations (GDPR, CCPA, internal retention policies)
• Partner with data governance to establish stewardship practices, certified datasets, and SLA expectations
• Partner with application engineering, data scientists, data analytics units to develop data products that unlock enterprise value
• Translate business requirements into scalable data architecture and reusable technical solutions
• Drive technical prioritization, sprint planning, and execution of the platform roadmap
• Mentor data engineers and act as the principal technical lead for engineering best practices
• Introduce modern engineering patterns
• Create documentation standards, operational runbooks, and incident response processes

Requirements:

• 7–10+ years in data & analytics engineering, platform engineering, data architecture or related technical fields
• Proven experience designing and operating modern cloud data platforms, especially Snowflake and DBT
• Strong understanding of Snowflake platform including advanced Snowflake features and Microsoft Azure, including data services, security and cost governance
• Hands‑on expertise with building data pipelines using tools such as Azure Data Factory, Fivetran, Matillion, or similar ingestion & ETL frameworks
• Proficiency in SQL, Python, and data modeling
• Strong understanding of data lifecycle management, DevOps practices, data orchestration, and production data operations
• Strong problem‑solving and systems thinking abilities
• Ability to work in fast‑moving environments with ambiguous or evolving requirements
• Excellent communication skills with the ability to simplify complexity for non‑technical audiences
• A mindset of automation, reusability, and continuous improvement
• Experience operating in organizations modernizing legacy data landscapes into a modern cloud data stack