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Cognito Therapeutics

Data Platform and Infrastructure Engineer

Posted 2 days ago
5-10 years experience
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AI Summary

The Data Platform Engineer will design and build cloud infrastructure, ingestion pipelines, and a data lakehouse architecture to centralize device, clinical, and business data. They will also enable analytics by setting up BI interfaces and integrating LLM-powered chatbots for stakeholders.

This is a rare opportunity to join a team that is bringing an entirely new category of brain health to the world. At Cognito, we are developing therapies designed to promote dignity, clarity, and coherence in the lives they touch.

Cognito is a neurotechnology company developing a new therapeutic approach to cognitive and neurological health, designed to work with the brain's own activity and biology. Born from pioneering neuroscience research at MIT, Cognito brings together neuroscience, engineering, medicine and technology to translate breakthroughs in brain science into practical therapies designed for everyday life.

Our first therapeutic application, Spectris AD, is an investigational, prescription, at-home therapy for Alzheimer's disease. With our pivotal HOPE study now complete, Cognito is entering an important new phase as we advance Spectris AD toward regulatory review, prepare for potential commercialization and continue exploring the broader potential of our science across neurological health.

We are building an interdisciplinary team united by a shared purpose: protecting and progressing the human ability to think, learn and remember. For innovators who want to work at the intersection of breakthrough science, technology and human health, Cognito offers the chance to help shape what comes next.

About the Job

Cognito is building a Security, Privacy, and IT organization from the ground up under the SVP of Security, Privacy, and IT, structured across three functions. The Data Platform Engineer is the hands-on technical role reporting directly to the IT Director's ownership of Cognito's data lake initiative. You'll build the cloud infrastructure, ingestion pipelines, and lakehouse architecture that bring together device, clinical, and business data into a single trusted platform — and then make that platform usable, both through a traditional analytics interface and through LLM chatbot interface.

Responsibilities

Cloud Data Infrastructure & Ingestion

  • Design and build the cloud infrastructure — compute, storage, and networking — underpinning Cognito's data platform, partnering with the IT Director on architecture and technology choices.

  • Build ingest points and pipelines that reliably bring data in from multiple sources — device and telemetry data, clinical and research data, and core business systems — into the central platform at scale.

Data Standardization & Interoperability

  • Help solve the technical challenges of getting disparate datasets to “speak the same language” — designing common data models, schemas, and data contracts so device, clinical, and business data can be joined and reasoned about together.

  • Establish data quality and validation checks at ingestion so downstream users and systems can trust the data.

Data Lakehouse Architecture

  • Own the technical setup of the data lakehouse — storage layout, table formats, partitioning, and compute engine configuration — balancing cost, performance, and ease of access.

  • Build pipeline reliability and observability practices — monitoring, alerting, and data quality checks — into the platform from the start.

  • Establish de-identification of data, ensuring proper handling of all Personally Identifiable and Protected Health Information

Analytics Platform Enablement

  • Stand up the analytics layer on top of the lakehouse — a semantic/metrics layer, curated data marts, and the infrastructure needed for self-serve analytics.

  • Partner with business, clinical, and data science stakeholders to understand their analytics needs and translate them into platform capabilities.

Data Output & Access — BI and AI Interfaces

  • Set up and support a traditional BI interface (dashboards and reporting) so business stakeholders can access insights without needing to write queries themselves.

  • Build, or lead the technical integration of, an internal chatbot.

Security, Governance & Cross-Functional Partnership

  • Ensure access controls, encryption, and data governance are built into the platform from the start, not bolted on later.

  • Document platform architecture and operational runbooks so the platform can scale as the team grows.

Qualifications

  • Bachelors degree in Computer Science, Software Engineering, or Information Systems with 5+ years building data platforms or data pipelines, including hands-on cloud infrastructure experience (e.g., AWS, Azure, or GCP) provisioning ingestion, storage, and compute for data workloads.

  • Experience designing and building data ingestion pipelines from multiple heterogeneous sources into a central platform.

  • Experience with data modeling or schema standardization work that makes disparate datasets interoperable (e.g., common data models, data contracts, or master data management).

  • Hands-on experience building a data lakehouse architecture (e.g., Delta Lake, Apache Iceberg, or a similar table format), including storage layout, partitioning, and query performance.

  • Experience standing up or supporting a BI/analytics layer (e.g., dashboards, a semantic layer, or self-serve analytics tooling).

  • Strong SQL and data engineering fundamentals — ETL/ELT, orchestration, and data quality practices.

  • Experience building or integrating an LLM-powered chatbot or natural-language interface over structured, unstructured, or analytical data.

Preferred

  • Experience with healthcare, clinical trial, or biosignal/medical device data specifically.

  • Experience building data platforms in a regulated environment (HIPAA, and eventually SOC 2/HITRUST).

  • Familiarity with data governance or data cataloging tools and data quality frameworks.

  • Experience partnering with data science or ML teams on productionizing analytics or AI features.

Other

  • Remote (USA) position; flexibility required during peak periods, which may include supporting critical infrastructure work outside normal business hours as needed.

Competitive Benefits

Taking care of our own is one of our highest priorities. That’s why we offer benefits including unlimited PTO, wellness perks, virtual medical support, and health, dental, and vision insurance.

Physical Requirements & Work Environment

• This role is primarily performed in an office or home-office setting. Essential physical requirements include the ability to work at a computer for extended periods, communicating effectively in written and verbal formats, and participate in video and in-person meetings.

• Occasional travel to partner sites may be required. For remote roles, occasional travel to Cognito’s Cambridge, MA office may also be required.

Cognito Therapeutics is committed to providing reasonable accommodation for qualified individuals with disabilities throughout the application and hiring process. If you require accommodation, please contact us at recruitingteam@cognitotx.com.

Cognito Therapeutics is an Equal Opportunity Employer. We are committed to building a diverse and inclusive workplace and make employment decisions based on qualifications, merit, business needs, and job requirements. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, genetic information, or any other characteristic protected by applicable federal, state, or local law.

All applicants must be legally authorized to work in the United States.

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