Lead Data Platform Engineer

College BoardRemote - Virginia, VA
$185,000 - $200,000Remote

About The Position

The External Data Analytics team builds and operates the data platform that powers trusted, timely analytics across College Board's exam and AP Classwork programs, including AP Classwork's continuous, year-round data needs. This is a small, closely knit, cross-functional team of approximately 7 engineers with a mix of data engineering and full-stack backgrounds. The team values ownership, thoughtful automation, clear documentation, pragmatic architecture, and keeping students top of mind in everything they build. As the technical lead for the platform, you will own architecture end-to-end and serve as the final technical authority on the team's hardest problems, operating at a level above a senior individual contributor. You will stay hands-on, writing production infrastructure-as-code and setting the coding standards the team follows, while leading design and implementation across streaming and batch ingestion, curated analytical data products, and reliable data-consumption patterns. The immediate priority is AP Classwork analytics, requiring design for continuous, steady-state, year-round throughput and long-running data quality, often working through ambiguity as requirements and priorities evolve. You will work with contributing domain teams to establish data contracts and ensure data is accurate, governed, secure, and ready for analysis, making and communicating tradeoffs involving scale, performance, reliability, cost, and operational complexity. You'll also set the standard for how the team uses AI-assisted coding responsibly, establishing review practices and guardrails for AI-generated code, and, as a technical anchor for the team, mentor engineers and raise engineering standards across the platform.

Requirements

  • Strong, current, hands-on coding experience in TypeScript and/or JavaScript with AWS CDK is required.
  • 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.

Nice To Haves

  • 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
  • familiarity with the education technology domain

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.

Benefits

  • meaningful career
  • supportive team
  • comprehensive package designed to help you thrive
  • fair and competitive compensation grounded in your qualifications, experience, impact, and the market
  • open, transparent conversations about compensation, benefits, and what it’s like to work at College Board throughout your hiring process
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