Engineer Data Intelligence/Business Analytics

Engineer Data Intelligence/Business Analytics

The Engineer, Data Management and Analytics designs and develops scalable ETL/ELT pipelines leveraging Snowflake, dbt, and Matillion, with a focus on healthcare data (including Epic). This role incorporates AI-driven techniques to improve data quality, pipeline efficiency, and intelligent data processing.

• Partner with Data Warehouse Product Owner and BSA to translate healthcare business requirements (including Epic data) into scalable ETL solutions.
• Collaborate with Data Architect to design Snowflake-based data models supporting analytics and AI use case.
• Build and maintain ETL/ELT pipelines using Matillion, dbt and Python to ingest and transform data from Epic Clarity, APIs, and third-party systems.
• Apply AI-driven techniques for automated data mapping, anomaly detection, and schema drift identification within pipelines.
• Develop reusable frameworks for logging, monitoring, and data quality validation using intelligent rules and pattern detection .
• Optimize Snowflake performance (partitioning, clustering, cost optimization) for both BI and AI workloads .
• Enable feature engineering by preparing curated datasets for downstream machine learning use cases .
• Leverage AI-assisted development tools to accelerate SQL/dbt/Python model development and pipeline automation.
• Implement data observability practices to proactively identify pipeline failures and data inconsistencies.
• Ensure compliance with healthcare data governance standards (HIPAA) and responsible AI usage.
• Other duties as assigned.

REQUIRED

• Bachelor's degree or equivalent experience.
• 2+ years in data engineering with strong ETL/ELT experience.
• Hands-on experience with Snowflake.
• Strong SQL skills and experience with dbt or Matillion.
• Experience building cloud-based data pipelines.
• Foundational understanding of AI/ML concepts related to data preparation and feature engineering.
• Experience with Git-based source control and CI/CD pipelines.
• Experience in data integration from disparate sources: third party vendor data and/or API calls.

PREFERRED

• Experience integrating Epic (Clarity/Caboodle) data models or related healthcare data .
• Experience in Microsoft SSIS.
• Experience with Microsoft Fabric
• Experience using Python for data integration and analysis.
• Experience with data observability tools and anomaly detection frameworks.
• Exposure to MLOps practices and model data pipeline support.
• Experience with Kafka or streaming ingestion frameworks
• Experience using AI copilots or automation tools in development workflows
• Experience with Cloud Lakehouse experience for any of the Cloud vendors (AWS, Azure, GCP)
• Experience with Enterprise orchestration tools – like Airflow, Dagster.

KNOWLEDGE/SKILLS/ABILITIES

• Strong problem-solving skills with ability to optimize complex ETL pipelines.
• Demonstrated excellent interpersonal, verbal and written communication skills.
• Detail oriented, organized, customer/process focused, problem resolution, and proactive.
• Ability to draw conclusions and make independent decisions with limited information.
• Ability to respond to common inquiries from customers, staff, regulatory agencies, vendors, and other members of the business community.
• Ability to be self-motivated, reliable, work independent, as part of a team, and work effectively with all levels within the organization.
• Demonstrated intellectual curiosity and willingness to adopt emerging AI technologies.
• Demonstrated change management in a fast-paced environment under time constraints.
• Ability to work with mathematical concepts: probability and statistical inference.
• Ability to effectively simplify complex data and communicate information to leadership.