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Role Description

The Senior Data & Platform Engineer is responsible for the day‑to‑day technical execution, reliability, and evolution of GID’s enterprise data platform. This role ensures the data foundation is scalable, secure, cost‑optimized, and ready to power analytics, AI, operational automation, and internal applications. The role spans hands‑on engineering, platform ownership, standards development, and technical leadership to accelerate data driven decision making across the organization. The Senior Data & Platform Engineer will embrace our company value of accountability, inclusiveness, energizing and courageousness.

Responsibilities

• Platform Ownership & Architecture
  • 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.
• Pipeline Engineering & Data Products
  • 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.
• Governance, Quality, and Controls
  • 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.
• Collaboration & Delivery
  • 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.
• Leadership & Team Development
  • 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.

Qualifications

• 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.

Compensation

Our company considers a range of factors including education and experience when determining base compensation. Compensation range: $175,000 - $200,000 plus 15% bonus potential.

Benefits

• Comprehensive benefits package, including medical, dental, vision, 401k, and PTO.
• 1 hour of paid sick and safe time for every 30 hours worked.
• 10 days of paid vacation time accrued bi-weekly.
• 6 weeks of paid parental leave.
• 10 paid holidays annually.
• Up to 3 floating days.