Design and implement scalable data pipelines for AI/ML workloads.
Develop and deploy AI/ML solutions using Python, Snowpark, or cloud-native ML services.
Build and manage feature stores to support model training and inference.
Integrate structured and unstructured data sources from internal and external systems.
Collaborate with data scientists to understand data requirements and optimize pipelines.
Implement data quality checks, metadata tagging, and lineage tracking.
Ensure compliance with Health Insurance Portability and Accountability Act (HIPAA), Centers for Medicare and Medicaid Services (CMS), and enterprise data governance standards.
Automate data ingestion and transformation using tools like AWS Glue, Snowflake, and Informatica Data Management Cloud (IDMC).
Implement DevOps/MLOps and Continuous Integration (CI)/Continuous Delivery (CD) pipelines using git actions or similar tools.
Monitor pipeline performance and troubleshoot issues in production environments.
Contribute to backlog grooming and sprint planning for AI data initiatives.
Perform other duties as assigned.

Requirements

Bachelor's Degree in Computer Science or Related Field
At least 5 years of experience in data engineering
At least 2 years of experience focused on AI/ML data pipelines
Hands on experience working on GenAI projects (chatbot implementations, Natural Language Processing (NLP), Sentiment Analysis, recommendation systems, anomaly detection etc)
Proficient skills in Python, SQL, Spark, AWS (Glue, S3, Lambda), Snowflake (Snowpark Container Services), IDMC, prompt engineering, model inference and fine-tuning, RAG and working with MCP, Vector databases
Solid understanding of supervised and unsupervised machine learning methods, feature engineering, model evaluation, and validation techniques
Ability to operationalize models in production environments, including basic MLOps practices (version control, CI/CD, reproducibility)
Ability to communicate complex AI/ML concepts effectively to non-technical stakeholders
Excellent documentation skills, ensuring reproducibility, clarity of assumptions, and transparency of model design
Strong collaboration skills, with proven ability to work cross-functionally with key stakeholders
Analytical problem-solving skills with the ability to translate business challenges into actionable AI/ML solutions
Effective written and verbal communication skills, including documentation of modeling processes, assumptions, and results

Benefits

Paid Time Off (PTO)
Tuition Reimbursement
Retirement Plans
Medical, Dental and Vision
Wellness Program
Volunteer Time Off (VTO)

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonSQLSparkAWSSnowflakeInformatica Data Management CloudNatural Language ProcessingSentiment Analysisfeature engineeringmodel evaluation

Soft Skills

communicationdocumentationcollaborationanalytical problem-solvingability to communicate complex conceptstransparencyclarity of assumptionscross-functional teamworkeffective written communicationeffective verbal communication

Certifications

Bachelor's Degree in Computer Science or Related Field