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Added 3 mins ago
C
Full Stack Engineer, Business Applications & AI
Chowbus
Chicago, IL
- $100,000 to $130,000 USD / year
We’re hiring an engineer to help build the customer lifecycle project, a high-priority platform that streamlines and scales our internal business workflows, from restaurant onboarding to…
Added 3 mins ago
Senior AI Engineer, Finance AI & Automation
BMO Bank N.A.
Chicago, IL
BMO is hiring a Senior AI Engineer to design, build and run production-grade AI solutions across Finance. You will own solutions end to end:
Added 7 mins ago
Sr. Technical Marketing Engineer
NetApp
Morrisville, NC
The CI Solutions team builds, validates, and launches NetApp data management, hybrid cloud, FlexPod, and next-generation AI infrastructure solutions. This role serves as a technical leader…
Added 7 mins ago
Sr Project Manager - AI Data Centers
Jacobs
Cary, NC
…Management firm globally (ENR, 2025). We are not riding the data center wave; we are engineering it. Jacobs’ Data Center Digital Twin solution, built on NVIDIA’s Omniverse DSX Blueprint,…
Added 7 mins ago
Research and Development Engineer 2
Cook Medical
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The Research and Development Engineer 2 will be a technical leader and/or growing subject matter expert, applying engineering principles to solve technical challenges and ensuring products…
Added 7 mins ago
O
Senior Manager - Quality Engineering
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· Analyze field performance and reliability data to identify improvement opportunities.
Added 7 mins ago
Principal Application Engineer- Financial Reporting
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Cybersecurity Engineer
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Added 7 mins ago
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Senior Java Full Stack Engineer – Spring Boot & AWS
Cognizant
Raleigh, NC
- $86,000 to $99,000 USD / year
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Added 7 mins ago
Gemini Enterprise for CX Sr. Engineer
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Added 7 mins ago
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Google Senior Data Engineer
Accenture
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- $94,400 to $266,300 USD / year
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Added 7 mins ago
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Google Data Specialist
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Google Cloud certifications (Associate Cloud Engineer or Professional Data Engineer).
Added 8 mins ago
Senior Power Management Engineer, Platforms Engineering
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Lead Principal Data Systems Software Engineer
Oracle
Redwood City, CA
- $122,800 to $306,400 USD / year
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Associate Project Leader, Naval Digital Infrastructure & Services
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Defensive Cybersecurity Engineer/Incident Response
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Defensive Cybersecurity Engineer/SOC SME
The Mitre Corporation
McLean, VA · Bedford, MA · Colorado Springs, CO · Fort Meade - Annapolis Junction, MD · Huntsville, AL · San Diego, CA · Tampa, FL
Design, develop, and refine security detections, analytics, and dashboards, and integrate new data sources into security information and event management (SIEM) platforms.

Absentia Labs

Senior Data Engineer

San Francisco, CA, United States
Boston, MA, United States
New York City, NY, United States
Seattle, WA, United States
San Jose, CA, United States
Austin, TX, United States

$125,000 to $160,000 USD / year

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Job details

Pay: $125,000 to $160,000 USD / year
Experience: 5+ years of experience in data engineering, platform engineering, or ML infrastructure roles, with clear ownership of production systems.
Posting language: English
Posted: Nov 5, 2026

Original job description

ABOUT ABSENTIA LABS

Absentia Labs is building the data and intelligence infrastructure that powers the next generation of biomedical discovery. We work at the intersection of biology, chemistry, machine learning, and large-scale systems, transforming fragmented scientific data into reliable, machine-learning-ready knowledge.

Biomedical data is dispersed, semi-structured, and inherently noisy, yet deeply interconnected across experiments, assays, compounds, and biological systems. Extracting value from this complexity requires deliberate schema design, principled abstractions, and rigorous post-processing pipelines that can support both scientific reasoning and large-scale AI.

We believe breakthroughs start with strong data foundations. This role sits at the architectural core of our platform, shaping how scientific data is modeled, validated, versioned, and served across the organization.

THE ROLE

As a Senior Data Engineer, you will own the design and evolution of Absentia Labs’ biomedical data platform. You will operate with a high degree of autonomy, making long-horizon architectural decisions while remaining hands-on in implementation.

This role is ideal for an engineer who enjoys working in high-ambiguity, research-driven environments, and who understands that data engineering for AI is as much about representation and correctness as it is about scale.

WHAT YOU’LL DO

Architect and lead the design of end-to-end data systems for large-scale biomedical datasets (chemical, biological, toxicology, omics, assay, clinical, and experimental data).
Define and evolve schema-driven data models that reconcile noisy, semi-structured, and heterogeneous sources into coherent, interoperable representations.
Establish best practices for data quality, validation, provenance, lineage, and versioning suitable for scientific and ML workflows.
Build and maintain cloud-native data infrastructure (data lakes, warehouses, object storage, streaming systems) with an emphasis on scalability and reliability.
Design pipelines that support both batch and streaming access for ML training, evaluation, and inference.
Partner closely with ML engineers, scientists, and product leads to translate research needs into durable data abstractions.
Make principled trade-offs around performance, cost, flexibility, and correctness in production systems.
Provide technical leadership through design reviews, architectural guidance, and mentorship of other engineers.
Identify and proactively address systemic risks in data integrity, scalability, and operational complexity.

WHO YOU ARE

You are a data engineer who thinks in systems and interfaces, not just pipelines. You are comfortable owning poorly defined problems and converging on robust solutions through thoughtful design and iteration.

You understand that biomedical data is rarely “clean,” and that schema design, normalization, and semantics are first-order engineering problems - especially in AI-driven settings.

YOU LIKELY HAVE

5+ years of experience in data engineering, platform engineering, or ML infrastructure roles, with clear ownership of production systems.
Proven experience designing and operating large-scale, production-grade data pipelines.
Strong proficiency in Python and data-centric software engineering practices.
Deep experience with cloud platforms (AWS, GCP, or Azure), including storage, compute, and security primitives.
Familiarity with distributed data processing and orchestration systems (e.g., Spark, Beam, Ray, Airflow, Dagster).
Experience supporting ML/AI workloads, including dataset generation, feature pipelines, and reproducible training workflows.
Strong architectural judgment and the ability to communicate technical decisions clearly across disciplines.

BONUS IF YOU HAVE

Competitive compensation, including meaningful equity participation, allows you to share directly in the long-term success and growth of the company.
Prior work with biomedical or life-science data (e.g., omics, assays, molecular representations, clinical or toxicology data).
Experience with streaming platforms (Kafka, Pub/Sub, Kinesis).
Exposure to ontology-aware data modeling or schema evolution in scientific domains.
Infrastructure-as-code and systems experience (Terraform, Docker, Kubernetes).
Experience in early-stage startups or research-heavy environments.
Open-source contributions or technical publications.

WHAT WE OFFER

A chance to architect the data backbone of an AI-driven biomedical platform.
Direct impact on how scientific data is translated into machine intelligence.
High autonomy, high trust, and ownership over critical systems.
Flexible remote or hybrid work arrangements.
A deeply technical, low-ego culture focused on learning and rigor.

HOW TO APPLY

Please submit your resume and a short note on why this role resonates with you. Links to GitHub, technical writing, or relevant projects are encouraged.

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More about this job

Skills

Research
Data engineering
Data models
ML
Leadership
Python
AWS
Google Cloud
Microsoft Azure
Process data
Apache Spark
Apache Airflow
Apache Kafka
Data modelling
Infrastructure as code
IBM Terraform
Docker
Kubernetes

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