Data Platform Engineering Lead

Position Summary

HASI is modernizing the technology foundation that powers data, analytics, AI, and business applications across the enterprise. We are seeking a Platform Engineering Lead to own and evolve that foundation and build the engineering discipline responsible for making it scalable, secure, automated, reliable, and cost effective.

This is a hands-on technical leadership role. You will own the architecture and roadmap for HASI's enterprise data platform, establish modern platform engineering and CI/CD practices, automate infrastructure and deployments, improve observability and operational reliability, and create reusable platform capabilities that allow data and product teams to move faster.

The role sits at the intersection of cloud infrastructure, data engineering, DevOps, security, and enterprise architecture. You will work across a technology ecosystem that includes Snowflake, Airflow, SQL Server, Power BI Service, SAP, JupyterHub, BusinessObjects and the broader data warehouse, integration, and metadata ecosystem.

Our operating model is intentionally clear: Platform Engineering owns the technology foundation. Data Engineering & Architecture owns the enterprise data and pipelines built on that foundation. BI & Data Products owns the business-facing analytical capabilities. Your job is to make the underlying platform exceptional.

This is an opportunity to take an existing enterprise technology landscape and transform it into a modern platform engineering capability. You will establish the architecture, engineering standards, automation, operating practices, and team that will support HASI's next generation of data, analytics, and AI capabilities.

Key Responsibilities

Platform Architecture & Roadmap: Own the architecture and multi-year roadmap for HASI's enterprise data platform, balancing business requirements, engineering needs, security, scalability, reliability, and cost.

Platform Engineering & Automation: Establish modern platform engineering practices across the environment, including CI/CD, infrastructure and configuration automation, deployment pipelines, testing, environment management, source control, and engineering standards.

Platform Reliability & Operations: Engineer platforms for production reliability. Establish observability, monitoring, incident response, change management, operational runbooks, capacity management, and other practices required to operate critical enterprise platforms at a high standard.

Security: Own the technical security of the data platform in partnership with Cybersecurity, including identity and access controls, data protection, secure configuration, auditability, and compliance with internal and regulatory requirements.

Performance & Cost Optimization: Continuously evaluate platform utilization, performance, scalability, reliability, and cost. Identify inefficiencies and architectural improvements and ensure HASI is getting appropriate value from its platform investments.

Integration Enablement: Design and enable reusable integration patterns and platform capabilities that allow Data Engineering, BI & Data Products, AI Product Engineering, and enterprise applications to connect to data and services efficiently and consistently.

Platform Standards & Lifecycle Management: Establish technical standards and best practices across the platform ecosystem and own upgrades, patching, migrations, version management, technical debt reduction, and end-of-life planning.

Metadata & Catalog Platforms: Own the technical platforms and capabilities that enable metadata management, data cataloging, lineage, and data discoverability across the enterprise, in partnership with Data Engineering & Architecture and Data Governance.

Engineering Leadership: Provide technical direction to platform engineers, establish a high engineering bar, mentor team members, and help build the Platform Engineering function as the organization grows.

Cross-Functional Partnership: Work closely with Data Engineering & Architecture, BI & Data Products, AI Product Engineering, Cybersecurity, enterprise applications, and business teams to understand requirements and translate them into durable platform capabilities.

Technology Strategy: Stay current with developments across cloud, data infrastructure, platform engineering, and developer tooling. Evaluate emerging technologies and lead build-vs-buy and vendor decisions based on capability, architecture, cost, security, operational complexity, and risk.

Platform Outcomes: Define and report on measures of platform health and maturity, including availability, performance, security, adoption, reliability, deployment efficiency, operational maturity, and cost optimization.

Required Qualifications

• 7+ years of experience in platform engineering, data engineering, cloud infrastructure, DevOps, or a closely related technical discipline, with demonstrated ability to deliver and operate complex production technology environments
• Demonstrated experience owning enterprise platform architecture and translating architectural direction into a pragmatic multi-year technology roadmap
• Deep hands-on experience with modern data platforms and cloud data architecture, ideally including Snowflake, Airflow, and modern cloud data warehouse or lakehouse technologies
• Strong coding fundamentals, with proficiency in Python or an equivalent language and the ability to build platform tooling, automation, integrations, and services rather than relying exclusively on manual administration
• Strong experience with CI/CD, infrastructure automation, deployment automation, source control, environment management, and modern software engineering practices
• Experience designing and operating reliable production platforms, including monitoring, observability, incident management, performance optimization, capacity planning, and operational automation
• Strong understanding of cloud and data platform security, including identity and access management, secrets management, data protection, auditability, and secure platform configuration
• Experience designing integrations and reusable platform capabilities that enable other engineering and product teams to build and deliver effectively
• Ability to operate across strategy and execution. You can zoom out to define platform architecture and long-term direction and zoom in to troubleshoot a failed deployment, investigate a performance issue, or improve an automation pipeline
• Proven ability to evaluate technology and vendor decisions across capability, architecture, cost, security, operational complexity, and long-term strategic fit
• Proven track record of operating cross-functionally, building trust with technical and non-technical stakeholders, and translating requirements into scalable technical solutions
• Exceptional drive and ownership mentality. You set a high bar, hold yourself accountable for outcomes, and take responsibility for the reliability and quality of the platforms you own
• Clear, direct communicator who can explain architecture, tradeoffs, platform performance, and investment decisions to both technical and non-technical audiences
• Strategic thinker with an operator's bias, comfortable establishing long-term direction while remaining close enough to the technology to understand how it actually works
• Entrepreneurial and improvement-oriented mindset. You are energized by building capabilities, eliminating repetitive work through automation, improving engineering maturity, and making complex technology simpler for the teams that depend on it

Preferred Qualifications

• Experience building or materially modernizing an enterprise data platform or Platform Engineering capability
• Experience with Snowflake administration and architecture, Apache Airflow, SQL Server, and cloud infrastructure
• Familiarity with enterprise analytics platforms such as Power BI Service, SAP Datasphere, SAP Analytics Cloud, Sigma, or similar technologies
• Experience with infrastructure-as-code and configuration management technologies
• Experience with data catalog, metadata management, lineage, observability, or related platform technologies
• Experience supporting platforms used by data engineering, analytics, machine learning, or AI engineering teams
• Experience working in financial services, investment management, or another regulated or data-intensive industry
• Experience providing technical leadership to a small engineering team while remaining hands-on