Data Engineer, AdeptID
AI-First Staffing Platform
$150-180k
Talent matching engine
Be an early applicant
Talent matching engine
21-100 employees
Be an early applicant
$150-180k
21-100 employees
Company mission
AdeptID’s mission is to make job mobility easier for all people, regardless of educational attainment.
Role
Who you are
- If you're motivated by solving data challenges at scale and excited to build and learn about high-performing AI systems, you'll thrive here
- 3–7 years of experience as a Data Engineer or related backend-engineering role focused on data systems
- Exposure to or interest in MLOps-model deployment, feature pipelines, and reproducible training environments
- Hands-on experience with AWS data technologies (S3, Glue, Lambda, Redshift, Athena, Step Functions, or similar)
- Familiarity with data-orchestration tools such as Airflow, Prefect, or Dagster
- Understanding of data modeling, storage optimization, and schema design for analytics or ML workloads
- Experience with operational monitoring of data environments and workflows
What the job involves
- Reports to: Head of Engineering
- We're seeking a mid-level or senior Data Engineer to build and evolve the data backbone of AdeptID's AI-first staffing platform
- Our systems process millions of talent and job records monthly, ensuring that data is reliable, high-quality, and secure
- You'll design production data pipelines, automate manual workflows, and work closely with software and data science teams to make machine-learning models production-ready
- This hands-on role combines immediate impact with long-term growth: you'll deepen your expertise in modern data infrastructure while gaining experience in MLOps, AI data pipelines, and infrastructure-as-code on AWS – all in a supportive, learning-oriented environment that values curiosity and shared success
- Design, build, and maintain scalable ETL and data pipelines in Python on AWS
- Automate manual data workflows to improve repeatability and speed
- Monitor and optimize pipelines for reliability, latency, and data quality
- Create code, systems, and policies for handling sensitive/PII information at scale
- Develop and maintain data environments with infrastructure-as-code on AWS
- Contribute to observability and performance monitoring – defining metrics and dashboards that highlight system health
- Partner with data scientists and ML engineers to develop data flows powering model training, evaluation, and inference
- Collaborate in reviews and design discussions to help set standards for data-engineering best practices
- Document schemas, transformations, and data lineage for transparency and maintainability
Application process
- Well-qualified candidates will be invited to submit short responses to a set of screening questions and meet with a member of the hiring team
Our take
Talent identification and acquisition has always been a challenge for HR teams, but the labor shortage is making it more difficult than ever. The founders of AdeptID believe that poor talent matching is a billion-dollar problem, and they’re aiming to address it with its machine-learning-powered API.
While there’s no shortage of talent search and matching platforms, from LinkedIn to Zoho Recruit, AdeptID sets itself apart by providing an API which plugs into existing infrastructure. Another interesting aspect of AdeptID’s approach is how its ML tech focuses on lesser-explored talent avenues, particularly candidates who don’t hold degrees and might otherwise be filtered out in other talent searches.
Having only launched in 2020, AdeptID's bootstrapped first year brought in an encouraging $1 million. Since then, it's been backed by Zeal Capital Partners, and the company has been scaling operations in the last couple of years. It is also a certified B-corp, and in 2023, partnered with OneTen to improve hiring outcomes for black talent in the US.
Kirsty
Company Specialist at Welcome to the Jungle
Company
Funding (1 round)
Dec 2021
$3.5m
SEED
Total funding: $3.5m
Company benefits
- Opportunity to join an exciting venture in its early stage
Company HQ
Financial District, Boston, MA
Leadership
Fernando Rodriguez-Villa
(Co-Founder & CEO)Was commercial lead and founding team member at satellite analytics company TellusLabs (acquired by Indigo). Became Indigo's Director of International Strategy post acquisition. Also worked in Business Development at adaptive learning company Knewton.
Brian DeAngelis
(Co-Founder & Chief Data Scientist)Served as a Data Scientist at Indigo before co-founding AdeptID. Previously worked as an Analyst at Opera Solutions, specializing in Machine Learning and Data Science. Co-founded the Hopewell Hockey Company in 2016.
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