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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Data Platform Engineer - **Company:** THECOLLEGECOACH L L C - **Location:** Reston, VA, United States (Remote available) - **Experience:** Expert - **Salary:** $185,000.0 - $200,000.0 - **Contract:** Permanent contract - **Skills:** JavaScript (Programming Language), Artificial Intelligence, Amazon Web Services, Amazon S3, Data Analysis, Architectural Patterns, Software as a Service, Data Architecture, Information Engineering, Data Infrastructure, Data Integrity, Amazon DynamoDB, TypeScript, AWS Cdk, Cloud Platform System, Grafana, Electronic Medical Records, Influxdb, Apache Flink, Data Analytics, Data Management, Tools for Reporting, Cloudwatch, Software Coding, Amazon Simple Queue Service (SQS), Data Pipelines - **Published:** September 2, 2026 - **Apply:** https://www.jofdav.com/jobs/59520715-lead-data-platform-engineer ## About the Role You bring experience across the capabilities below. We do not expect candidates to have worked with our exact tool stack for everything; comparable tools and the judgment to map your experience onto ours quickly matter. * 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. * 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., * 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 ## Description 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. We're a small, closely knit, cross-functional team (~7 engineers today, and growing) with a mix of data engineering and full-stack backgrounds. We value ownership, thoughtful automation, clear documentation, pragmatic architecture, and keeping students top of mind in everything we build. About the Opportunity As the technical lead for the platform, you'll own architecture end-to-end and serve as the final technical authority on the team's hardest problems, operating a level above a senior IC. You'll stay hands-on yourself, 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. Because our immediate priority is AP Classwork analytics, you'll be designing for continuous, steady-state, year-round throughput and long-running data quality, often working through ambiguity as requirements and priorities evolve; not just a single test-day spike. 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 along the way. 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. In this role, you will: * 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. ## Related Videos - [5 steps for running a Kubernetes environment at scale](https://www.wearedevelopers.com/videos/88-5-steps-for-running-a-kubernetes-environment-at-scale) - [Building Reliable Serverless Applications with AWS CDK and Testing](https://www.wearedevelopers.com/videos/812-building-reliable-serverless-applications-with-aws-cdk-and-testing) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [All your telemetry data from any source in one place](https://www.wearedevelopers.com/videos/57-all-your-telemetry-data-from-any-source-in-one-place) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [The power of Cloud Development Kit (CDK): How to get the most out of it](https://www.wearedevelopers.com/videos/740-the-power-of-cloud-development-kit-cdk-how-to-get-the-most-out-of-it) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs)