Data Quality and Architecture Engineer
About ESHYFT
Nearly 1.3 million Americans are residents of nursing homes, and they depend on nursing staff for basic needs. Currently, 99% of nursing homes in the US are facing nursing shortages, which means residents may not receive adequate care.
We’re on a mission to provide health care to the most vulnerable by connecting nurses to healthcare facilities. We’re a technology company that strives to empower nurses by offering flexibility and control over when and where they work, along with higher wages. Through our mobile apps, our community of qualified nurses provide much-needed staff for short-staffed facilities.
About this role
The Data Quality and Architecture Engineer at ESHYFT will ensure our data systems’ accuracy, consistency, and scalability. This role combines data quality assurance with a strong focus on data architecture, modeling, and pipelining. You will be responsible for designing robust data pipelines, validating workflows, and supporting cross-functional teams with strategic data solutions.
Qualifications
Experience
- 3+ years of experience in data engineering, architecture, or quality assurance.
- Proven experience in data modeling, pipeline validation, and architecture design.
- Hands-on experience with tools like dbt, relational databases (e.g., PostgreSQL, MySQL), and Salesforce workflows.
Technical Skills
- Strong understanding of SQL, ETL/ELT processes, and data integration workflows.
- Expertise in building and deploying custom APIs for data pipelines, with proficiency in languages like Python or JavaScript.
- Experience with API development frameworks (e.g., Flask, FastAPI, Node.js).
- Proficiency with cloud data platforms (e.g., BigQuery, Snowflake) and orchestration tools (e.g., Airflow, Mage).
- Familiarity with CI/CD pipelines, version control (e.g., Git), and automation frameworks.
- Knowledge of observability tools for monitoring data quality and pipeline health.
Soft Skills
- Excellent communication skills for collaborating across teams and presenting complex data concepts.
- Analytical mindset with attention to detail to identify and resolve data quality issues.
- Self-motivated and adaptable to a fast-paced, evolving environment.
- Professionalism in correspondence with stakeholders.
Responsibilities
Data Architecture and Modeling
- Design and maintain scalable data models to ensure optimal performance and usability for analytics and downstream systems.
- Define and implement best practices for data governance, including lineage, cataloging, and documentation.
- Collaborate with data engineers to optimize ETL/ELT processes for reliability and performance.
Data Quality Assurance
- Develop and execute data validation frameworks, ensuring accuracy and consistency across pipelines and workflows.
- Create and maintain unit tests, integration tests, and regression tests for data systems, including dbt models and Salesforce workflows.
- Monitor data pipeline health using observability tools or custom monitoring scripts to proactively address data issues.
API Development and Pipeline Engineering
- Design and implement custom APIs for data integration and pipeline automation.
- Build, test, and deploy end-to-end data pipelines to integrate disparate data sources into cloud platforms like BigQuery.
- Write efficient, scalable code for data ingestion, transformation, and delivery in dbt.
- Optimize pipeline performance, ensuring low-latency and high-reliability data flows.
Collaboration and Communication
- Partner with developers, product managers, and analytics teams to understand data requirements and workflows.
- Support integration of marketing and analytics tools (e.g., Braze, Mixpanel, GrowthBook) with reliable data pipelines.
- Document and communicate data lineage and data dictionary updates for business and technical stakeholders.
Continuous Improvement
- Automate data testing and monitoring processes to improve efficiency and reduce manual effort.
- Stay updated with the latest data architecture, pipeline development, and quality assurance trends, applying them to enhance system performance.
- Suggest architectural improvements to prevent downstream disruptions and ensure data scalability.
Why Join Us?
- Be part of a mission-driven organization solving critical healthcare challenges.
- Contribute to building a robust data infrastructure that powers impactful insights.
- Grow your career with competitive pay, benefits, and opportunities for professional development.
Benefits (for US-based, W-2 employees)
- Weekly Pay
- Paid Holidays
- Paid Time Off
- Health Insurance
- Dental Insurance
- Vision Insurance
- Life Insurance
- HRA and FSA Accounts
401k with 10% Employer Match (Match is 10% of the employee’s contribution in the calendar year)
Salary range
$60-130k commensurate with experience