Data Engineer at TruDataRx

Norwich, Vermont, United States -

Full Time

Start Date

Immediate

Expiry Date

24 Mar, 26

Salary

0.0

Posted On

24 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, SQL, Snowflake, dbt, Python, Data Quality, Collaboration, Mentorship, Data Governance, ELT Architecture, Data Transformation, Orchestration, Version Control, Master Data Management, Healthcare Data, Cloud Services

Industry

Hospitals and Health Care

Description

Description ABOUT TRUDATARX TruDataRx, Inc. uses objective clinical data to help clients improve the clinical efficacy and reduce the costs of pharmacy benefits for its members. We are independent from all players in the pharmaceutical manufacturing and distribution industries, enabling us to best serve our clients. We value the following characteristics in our team members: Outward Mindset – foundation of our culture, which influences the right behaviors, that leads to results Entrepreneurial – the ability to get things done with resources you don’t control Humility – deep comfort in knowing when you don’t know and asking questions Collaboration – we always give benefit of doubt that each person has something to contribute POSITION SUMMARY: We are seeking an experienced Data Engineer to architect, build, and maintain our next-generation data pipelines. You will be the technical subject matter expert on our Modern Data Stack, primarily utilizing Snowflake and dbt. You will be responsible for defining best practices, conducting code reviews, and actively nurturing the growth of junior engineers. You will act as a bridge between raw data and actionable analytics, ensuring our analysts and data scientists have clean, reliable, and timely data. ESSENTIAL FUNCTIONS ELT Architecture: Design and build robust, scalable ELT pipelines to ingest data from various sources (APIs, production databases, third-party tools) into Snowflake. Data Transformation (dbt): Own the dbt project structure. specific responsibilities include: Developing complex SQL-based data models (incremental models, snapshots). Writing Jinja macros to keep code DRY (Don't Repeat Yourself). Implementing data quality tests (schema tests, custom data tests). Snowflake Optimization: Manage the Snowflake environment to ensure cost-efficiency and performance. This includes warehouse sizing, clustering strategies, and utilizing features like Snowpipe and Zero-Copy Cloning. Data Quality & Governance: Champion data integrity. Implement observability tools and alerts to catch pipeline failures or data anomalies before they reach the business users. Mentorship: Act as a technical lead for junior engineers, conducting code reviews, and establishing best practices for SQL and version control. Collaboration: Translate business requirements from Product and Analytics teams into technical specifications and data models Requirements REQUIREMENTS Required education: Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field (or equivalent practical experience). Required industry experience or certification: 3+ years of professional experience in Data Engineering and Database Development with medical and prescription claims Specific Stack Experience: 2+ years of hands-on experience specifically with Snowflake (architecture, snowpipe, streams/tasks, and security). 1+ years of production experience with dbt (developing packages, macros, and incremental models). Preferred skills: SQL Mastery: Expert-level SQL skills with the ability to write complex, highly optimized queries. You can write complex, performant queries and debug spaghetti code with ease. Deeply familiar with Snowflake architecture, including separation of storage and compute, semi-structured data handling (JSON/Variant), and security management (RBAC). Programming: Proficiency in Python for scripting, custom connectors, or orchestration tasks. Orchestration: Experience with workflow orchestration tools (e.g., Airflow or FiveTran, dbt or dbt Cloud). Version Control: Strong familiarity with Git flows and CI/CD pipelines for data (e.g., GitHub Actions, GitLab CI). dbt Proficiency: Strong experience with dbt (Core or Cloud). You understand the difference between ephemeral, table, and view materializations and know how to use dbt for documentation and lineage. Data Governance principles and best practices Master Data Management principles and best practices Preferred Qualifications (Bonus) Experience with database management Experience handling healthcare data formats (e.g. Pharmacy Claims data, Eligibility data, Medical Claims data, etc.). Knowledge of Azure/GCP services or similar AWS core services (S3, Lambda, IAM). Experience migrating legacy stored procedures to modern dbt models. Python: Proficient in Python for scripting, API interaction and Streamlit apps Version Control: Strong understanding of Git workflows (branching, merging, pull requests) specifically within a data context. Company Standard Requirements: Ability to work well with others in a collaborative environment Ability to get things done with resources you don’t control Willingness to admit you don’t know and ask for help Exhibit constant curiosity and a drive to problem solve Exhibit desire to learn and grow on a continuous basis

Responsibilities

The Data Engineer will architect, build, and maintain data pipelines, ensuring clean and reliable data for analysts and data scientists. They will also define best practices and mentor junior engineers.