Start Date
Immediate
Expiry Date
19 Nov, 25
Salary
0.0
Posted On
20 Aug, 25
Experience
5 year(s) or above
Remote Job
Yes
Telecommute
Yes
Sponsor Visa
No
Skills
Transformation, Data Security, Sql, Spark, Python, Supply, Product Classification, Azure, Aws, Oasis
Industry
Information Technology/IT
August 19, 2025
Role: Data Engineer – AI/ML Pipeline Focus
Employment Type: C2C
Client: REI Systems – FDA Account
Location: Remote, USA
No. of Positions: 2
Work Experience: 5+ Years of experience
Educational Qualifications: BS in Engineering, Computer Science, Information Systems or equivalent
Visa & Work Authorization: US Citizen/Green Card Holder/H1B/GC-EAD
Residency: Must have lived in the U.S. for at least 1095 days (3 years).
Security Clearance Requirements: Eligible to obtain Public Trust Clearance
Work Location: Hybrid or Remote for very strong candidates
Contract Duration: 6 months, extendable up to 1 year.
Interview Process: Two technical rounds (Including 1 coding round) followed by client interaction – Virtual Interviews
SKILLS & EXPERIENCE REQUIREMENTS:
5+ years of experience designing, developing, and maintaining large-scale data pipelines for AI/ML workloads.
Strong proficiency in Python and SQL, with experience in distributed processing frameworks (Spark, Databricks).
Hands-on experience with data ingestion, transformation, and feature engineering from heterogeneous sources (structured, unstructured, graph-based).
Familiarity with cloud data platforms (AWS, Azure, or GCP) and CI/CD practices for data workflows.
Experience working in regulated environments (e.g., healthcare, government) with knowledge of data security, lineage, and compliance requirements.
Preferred Qualifications:
Prior experience with FDA imports, customs, or supply chain data pipelines.
Familiarity with entity resolution, product classification, and risk scoring systems.
Experience building ingestion and transformation logic for regulatory datasets such as OASIS, PREDICT, or Center-specific compliance databases.
Knowledge of handling sensitive government data in compliance with FedRAMP and FISMA.
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