Data Engineer (AI/ML)

Blue Cross Blue Shield Association
Chicago, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 139K

Job location

Chicago, United States of America

Tech stack

Artificial Intelligence
Airflow
Amazon Web Services (AWS)
Azure
Clinical Data Repository
Cloud Computing
Cloud Engineering
Code Review
Data as a Services
Data Architecture
Data Cleansing
Information Engineering
Data Infrastructure
ETL
Data Security
Data Warehousing
Relational Databases
DevOps
Distributed Data Store
Python
Machine Learning
Meta-Data Management
NoSQL
Performance Tuning
SQL Databases
Data Processing
Fast Healthcare Interoperability Resources
Snowflake
Prompt Engineering
Electronic Medical Records
Generative AI
PySpark
Kubernetes
Information Technology
Amazon Web Services (AWS)
Health Level Seven International
Software Version Control
Data Pipelines
Databricks

Job description

The Data Engineer will design, build, and optimize scalable, secure data pipelines that power analytics and product platforms. For this role specifically, the focus will be on Machine Learning (ML) and Generative Artificial Intelligence (GenAI) workloads, while contributing to innovation and ensuring compliance with healthcare industry standards. This role is expected to provide strong hands-on technical expertise, collaborate across teams, and contribute to architecture decisions that align engineering practices with organizational goals., * Design, build, and maintain reliable, high-performance data pipelines for large-scale structured and unstructured healthcare data.

  • Use PySpark and modern cloud-based tools (Databricks, AWS Glue, EMR, Snowflake) to transform and process data efficiently.

  • Support ingestion, transformation, and validation processes that ensure data consistency, integrity, and availability.

  • Partner with Data Architects, Data Scientists, and Analysts to translate business needs into scalable engineering solutions.

  • Collaborate with platform and DevOps teams to deploy, scale, and monitor data pipelines using Airflow and Kubernetes.

  • Participate in code reviews, documentation, and continuous improvement efforts across the engineering team.

  • Implement and maintain data validation frameworks to ensure pipeline accuracy and completeness.

  • Contribute to best practices in version control, metadata management, and reproducibility.

  • Stay current with emerging technologies in data engineering and cloud computing, recommending improvements to existing infrastructure.

  • Participate in performance tuning, cost optimization, and scaling strategies for cloud-based data systems.

  • Identify automation opportunities to streamline ETL/ELT processes and reduce operational overhead.

  • Share knowledge and mentor junior team members on tools, techniques, and best practices.

  • Promote a culture of collaboration, innovation, and continuous learning within the engineering organization.

  • Support compliance with SOC 2, HIPAA, and GDPR by adhering to established data privacy and security practices.

The posting range for this position is: 100,800.00 - 138,600.00

Requirements

  • Bachelor's or Master's degree in Computer Science, Engineering, or related field., * 5+ years of experience in data engineering, including building and managing pipelines in cloud-based environments., * Experience with building and operationalizing the data foundations that support machine learning and generative AI use cases, including feature pipelines, training/inference data preparation, and retrieval-ready datasets (e.g., embeddings and vector stores)

  • Familiarity with GenAI skills and adjacent tooling (foundation models, prompt engineering, RAG, embeddings/vector databases, and GenAI orchestration frameworks).

  • Hands-on experience with AWS AI/ML and data services, including Amazon Bedrock, Bedrock Agent Core, SageMaker, Glue, and EMR.

  • Experience designing and optimizing data architectures, including data foundations that support ML and GenAI workloads.

  • Hands-on experience with workflow orchestration (Airflow) and containerization (Kubernetes).

  • Hands-on technical expertise, cross-team collaboration, and contributing to architecture decisions

  • Proficiency in Python, SQL, and distributed data frameworks (PySpark, Databricks, AWS Glue, EMR).

  • Working knowledge of cloud platforms (AWS or Azure) and data warehouses (Snowflake).

  • Familiarity with NoSQL and relational databases, as well as data modeling best practices.

  • Strong analytical, problem-solving, and communication skills.

  • Understanding of compliance frameworks (SOC 2, HIPAA) and secure data management principles.

  • Experience working with healthcare datasets or knowledge of healthcare standards (HIPAA, HL7, FHIR) preferred., The posted salary range is the lowest to highest salary we, in good faith, believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the hiring range and this hiring range may also be modified in the future. A candidate's position within the hiring range may be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, relevant experience, skills, seniority, performance, shift, travel requirements, and business or organizational needs. This job is also eligible for annual bonus incentive pay.

Benefits & conditions

$100,800 - $138,600 a year Health insurance, 401(k) matching, Paid time off, Vision insurance, Dental insurance, Paid holidays Full-time Chicago, IL 60601, We offer a comprehensive package of benefits including paid time off, 11 holidays, medical/dental/vision insurance, generous 401(k) matching, lifestyle spending account and many other benefits to eligible employees.

Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, or any other form of compensation that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company's sole discretion, consistent with the law.

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