Note: The job is a remote job and is open to candidates in USA. NBME is a not-for-profit organization that specializes in the creation of assessments and learning tools for physicians and health professionals. They are seeking a Senior Data Engineer to join their team, where the individual will modernize and optimize NBME's data platform, build data lakes, and support analytics and AI/ML initiatives.
Responsibilities
- Code, test, deploy, orchestrate, monitor, document, and troubleshoot cloud-based data engineering processes, feature stores, and vector databases in accordance with best practices and security standards throughout the development lifecycle
- Partner closely with data scientists, AI researchers, data and enterprise architects, and business stakeholders to identify, extract, clean, and format structured and unstructured data for AI/ML model training, fine-tuning, and feature extraction
- Lead evaluation, research, and experimentation efforts with batch and streaming data technologies, LLM data preparation frameworks, and MLOps tools to keep pace with industry innovation
- Act as a technical lead to showcase the capabilities of emerging AI and data technologies, enabling the widespread adoption of modern data techniques across the organization
- Significantly contribute to the definition and refinement of processes and procedures for the data engineering practice
- Educate and develop ETL developers on data engineering cloud-bases initiatives to enable transition to data engineer and practice
- Assures the integrity and accuracy of the corporate data, with particular attention to data security
- Responsible for ensuring high data quality for Data Services, Analytics and Master Data Management
- Helps coordinate technical solutions, takes responsibility for designs, development, testing and delivery of solutions
- Build automated, scalable, test-driven data pipelines
- Utilize software development practices such as version control via Git, CI/CD, and release management to enhance existing CI/CD pipelines in AWS
- Collaborate with Data Engineers, DevOps engineers and architects on improvement opportunities for DataOps tools and frameworks
Skills
- Bachelor's Degree
- At least 7 years of experience in application development (Internship experience does not apply)
- At least 4 years of experience in big data technologies
- At least 4 years' experience with cloud computing using AWS
- 4+ years of experience in application development including Python, SQL, Scala, or Java
- 4+ years' experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, MySQL etc.)
- 4+ year experience working on real-time data and streaming applications
- 4+ years of experience with NoSQL implementation (Mongo, Cassandra)
- 4+ years of data warehousing experience (Redshift)
- 6+ years of experience with UNIX/Linux including basic commands and shell scripting
- 7+ years of experience with Agile engineering practices
- 7+ years of experience with SQL optimization
- 4+ years of experience with PySpark
- 3+ year of experience with process orchestration including AirFlow, KubeFlow, AWS step functions, or Luigi
- Proven experience implementing Generative AI, LLM data preparation pipelines, and Vector Databases (e.g., Pinecone, Milvus, pgvector)
- Strong experience building and maintaining Feature Stores for machine learning models
- Experience building highly scalable, secure, and production-ready APIs and Data-as-a-Service (DaaS) platforms
- AWS Certified Data Engineer or AWS Certified Machine Learning – Specialty certifications
- 3+ year of experience with Machine Learning
- Experience with building a Data-as-a-service platform
- Experience with building APIs
Benefits
- Healthcare, Dental, Prescription, and Vision plans
- 401(k) w/match
- Tuition Reimbursement Plan
- Commuter Benefit: Public Transit or Parking options
- Remote Friendly Workplace
Company Overview
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