Lead Data Platform Engineer

College Board is a mission-driven organization that expands educational and career opportunities through technology and assessment programs. The Lead Data Platform Engineer will own the architecture, technical direction, and reliability of an enterprise data and analytics platform, while remaining hands-on in infrastructure-as-code, streaming and batch pipelines, data governance, and platform operations. The role also leads engineering standards, responsible AI-assisted coding practices, incident response, and mentorship across the team.

Responsibilities:

• Own the technical direction, architecture, evolution, and reliability of a shared enterprise data and analytics platform, serving as the team's final technical authority and escalation point
• Lead the hands-on design and implementation of streaming and batch data pipelines supporting real-time and historical analysis, independently writing production infrastructure-as-code (CDK/TypeScript)
• Design curated, governed analytical data products that provide consistent and trusted information for reporting and decision-making, including for a continuous, year-round data load rather than single-event spikes
• Ensure the platform can scale efficiently while meeting expectations for performance, availability, reliability, and cost, including safe recovery from retries and failures
• Establish data contracts with contributing teams, including expectations for schemas, data quality, service levels, and change management
• Embed security, access controls, lineage, classification, auditability, monitoring, and operational readiness into the platform
• Partner with domain, product, operations, security, and governance stakeholders to translate business and reporting needs into sustainable technical solutions
• Lead code and design reviews, set and enforce coding standards, mentor engineers across varying experience levels, and promote strong practices in data engineering, automation, observability, and platform reliability
• Establish and enforce responsible AI-assisted coding practices for the team, including reviewing AI-generated code and setting guardrails so AI-assisted development doesn't compromise shared infrastructure
• Respond to incidents and drive platform reliability across the team's services
• Evaluate emerging tools and architectural patterns and recommend changes when they improve outcomes, simplify operations, or reduce risk

Requirements:

• Strong, current, hands-on coding experience in TypeScript and/or JavaScript with AWS CDK is required. You'll be writing production infrastructure-as-code yourself and setting the coding standards the rest of the team follows from Day 1, not just reviewing architecture from a distance
• Demonstrated experience owning, not just contributing to, the technical direction and architecture of a scalable cloud data platform in production; you can point to a specific system you were accountable for end-to-end, built on technologies such as Kinesis, Data Firehose, Flink, Lambda, EventBridge, SNS/SQS, Redshift, Athena, Glue, EMR, S3, DynamoDB, or comparable
• Strong experience with analytical data modeling and curated, layered data architectures (e.g., medallion-style), plus monitoring/observability (CloudWatch, Grafana, InfluxDB, or similar) as a core part of platform design
• A track record of designing for scalability, performance, cost efficiency, data integrity, and safe recovery from retries or failures; you've personally debugged issues like out-of-order processing, duplicate delivery, or hot partitions in production
• Experience establishing data contracts and implementing schema evolution, data quality, access control, classification, lineage, and auditability practices
• A strong point of view on how to use AI coding tools responsibly at the team level, able to set guardrails and review standards, not just use the tools personally
• Demonstrated success of mentoring engineers, leading code and design reviews, being the escalation point on hard problems, and communicating across technical and nontechnical teams
• A passion for expanding educational and career opportunities and mission-driven work
• Curiosity and enthusiasm for emerging technologies, with a willingness to experiment with and adopt new AI-driven solutions and comfort with learning and applying new digital tools independently and proactively
• Clear and concise communication skills, written and verbal
• A learner's mindset and a commitment to growth: welcoming diverse perspectives, giving and receiving timely, respectful feedback, and continuously improving through iterative learning and user input
• A drive for impact and excellence: solving complex problems, making data-informed decisions, prioritizing what matters most, and continuously improving through learning, user input, and external benchmarking
• A collaborative and empathetic approach: working across differences, fostering trust, and contributing to a culture of shared success
• Authorization to work in the United States
• Helpful but not required: SaaS/multi-tenant or cell-based architecture, DuckDB, ML/AI-enabled analytics tools (e.g., SageMaker), a regulated/high-governance data environment, experience hiring or growing a data team, presenting technical roadmaps to non-technical stakeholders, multi-account AWS at org scale, or familiarity with the education technology domain