ESHYFT ยท 20 hours ago
Data Quality and Architecture Engineer
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Responsibilities
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.
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.
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.
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.
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.
Qualification
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Required
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.
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.
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.
Benefits
Weekly Pay
Paid Holidays
Paid Sick Leave
Health, Dental, Vision and Life Insurance
Supplemental Benefits including Accident, Hospital and Cancer Care coverage
Health Reimbursement Account
Health and Dependent Care FSA
401k with 10% match
401(k)
401(k) matching
Dental insurance
Flexible spending account
Health insurance
Life insurance
Paid time off
Referral program
Vision insurance
Company
ESHYFT
Eshyft is an app that offers an online marketplace to connect CNAs, LPNs, and RNs with flexible shifts at nearby nursing facilities.
Funding
Current Stage
Early StageRecent News
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