Data Engineer / Data & AI Engineer
Trulogik
- Location
- Onsite (Catonsville, Maryland)
- Employment
- Full-time
- Level
- Mid Level
Posted 3 days ago
About the role
Trulogik is modernizing U.S. health insurance operations through AI-powered automation. This role involves building scalable data pipelines and models to support healthcare payer operations and AI-driven products.
Skills
Python
SQL
Data Engineering
ETL/ELT
Data Modeling
Cloud Platforms
Azure
AWS
Databricks
Snowflake
Redshift
Spark
Data Pipelines
Healthcare Data
AI/ML
Schema Design
Full job details
Data Engineer / Data & AI Engineer – Health Insurance
We are seeking a hands-on Data Engineer / Data & AI Engineer to build scalable data pipelines and analytical data models that support healthcare payer operations and AI-driven products.
The ideal candidate combines strong data engineering, ETL/ELT, and data modeling skills with some exposure to AI/ML and modern data platforms. Experience in health insurance or healthcare payer data is strongly preferred.
Responsibilities
- Design and build scalable data pipelines, ETL/ELT workflows, and data integration frameworks.
- Develop and maintain analytical and operational data models for claims, provider, member, pharmacy, and related healthcare data.
- Work with structured and semi-structured data across APIs, databases, files, and cloud platforms.
- Ensure data quality, lineage, performance, reliability, and observability across pipelines.
- Support AI/ML use cases by preparing data sets, feature pipelines, inference data flows, and model-ready data.
- Collaborate with AI, product, and engineering teams to operationalize data-driven solutions.
- Work with business and domain teams to translate healthcare requirements into scalable data architectures.
Requirements
Qualifications
- 3+ years of experience in data engineering, ETL/ELT, or data platform development.
- Strong hands-on experience with Python, SQL, data pipelines, APIs, and relational/data warehouse technologies.
- Experience with cloud data platforms and tools such as Azure, AWS, Databricks, Snowflake, Redshift, Spark, or similar.
- Strong understanding of data modeling, schema design, transformation, and data quality.
- Exposure to AI/ML, LLMs, feature engineering, or ML pipelines is preferred.
- Experience with health insurance / healthcare payer data, particularly claims, provider, member, pharmacy, or eligibility data, is highly preferred.
- Strong analytical and problem-solving skills with the ability to work in a fast-moving product environment.
This role is ideal for someone who sits at the intersection of data engineering, healthcare data, and applied AI.