Director, AI & Data Platform Engineer

About Us

At ENFRA, we blend a rich history with a forward-looking vision. With over 100 years of experience, we are a pillar of stability in the energy infrastructure industry and a leader in innovative energy solutions. Our commitment to leveraging emerging technologies ensures that we remain at the forefront of the Energy-as-a-Service sector.

We believe in growth—not just for our business, but for our people. Our team members have the opportunity to advance their careers in a supportive environment that values continuous learning and development. We embrace innovation and encourage creative problem solving to tackle the energy infrastructure and energy challenges of tomorrow.

Inclusion is at the heart of our culture. We strive to create a workplace where every voice is heard and valued, fostering a collaborative environment where diverse perspectives drive our success.

Join us to be part of a legacy of excellence and a future of groundbreaking advancements. At ENFRA, stability, innovation, and growth are more than just values—they are the pillars of our continued success.

Overview

ENFRA is building a Modern Data and AI platform as the gravitational center of its transformation into an AI native enterprise. To lead this effort, we are establishing a Director, AI & Data Platform Engineer reporting directly to the VP, AI & Data Platform Engineer. The target-state platform uses a lakehouse-style landing zone for raw and standardized enterprise data (bronze/silver) and a modern cloud data warehouse as the system of record for curated, business-ready data marts (gold). This role owns the architectural patterns and operating model that move data reliably from landing through curation, governance, and consumption.This is a senior strategic technical leadership role with direct reports. It is designed as a player coach position that combines deep hands-on platform architecture with enterprise influence and people leadership. The Principal Architect owns the delivery of ENFRA’s modern data and AI platform from foundational architecture through production readiness and business enablement.This role sits above the business applications that integrate their data into the enterprise platform and below the business product owners who depend on the platform for analytics, reporting, and AI agents. Success is measured by whether the platform is usable, trusted, and actively accelerating business outcomes.

Responsibilities

Job Responsibilities

• Own the end-to-end architecture and delivery of ENFRA’s Modern Data and AI platform, including the lakehouse landing zone (bronze/silver) and curated enterprise data warehouse and marts (gold).
• Translate enterprise data and AI strategy into a secure, scalable, production-ready platform supporting analytics, reporting, and AI agents, anchored by Microsoft Fabric/OneLake and Snowflake.
• Define and evolve platform reference architecture across ingestion, landing, standardization, curation, semantic layers, AI integration, and consumption patterns.
• Establish standards for data ingestion from source systems, including data contracts, metadata requirements, observability, lineage, quality checks, and change management.
• Partner with application teams to ensure reliable, governed pipelines and promotion of curated outputs into Snowflake as business-ready data marts.
• Enforce architectural guardrails to prevent platform fragmentation, duplicated datasets, and unmanaged point solutions.
• Design the platform for incremental onboarding of new data domains as the enterprise portfolio evolves.
• Influence and guide enterprise data modeling, semantic layer design, and reusable data product structures.
• Enable business product owners to easily consume the platform for reporting, dashboards, advanced analytics, and AI agents.
• Serve as the architectural bridge between raw and standardized data in the lakehouse and curated Snowflake marts.
• Define and enable platform-level capabilities for applied AI, generative AI, and agent-enabled workflows.
• Establish standardized integration patterns for models, prompts, orchestration, and inference services.
• Partner with data science and AI engineering teams to operationalize models without embedding platform logic in individual solutions.
• Embed governance, security, compliance, monitoring, lifecycle management, and cost controls directly into platform architecture.
• Act as the architectural authority for all data and AI platform decisions across the enterprise.
• Lead and grow a small, high-impact team of data and AI platform engineers or architects.
• Operate as a player-coach, remaining hands-on while establishing delivery practices, architectural reviews, and escalation paths.
• Provide architectural leadership for Snowfla