Foundational Data Engineer
HelpGrid
full-time
Posted on:
Location Type: Remote
Location: Remote • 🌎 Anywhere in the World
Visit company websiteJob Level
Mid-LevelSenior
Tech Stack
Amazon RedshiftAWSAzureETLMicroservicesNode.jsPythonSQL
About the role
- Evaluate and restructure existing data architecture to support scalability and performance
- Design new schemas, relationships, and data models that align with business logic and analytics needs
- Build and maintain a HelpGrid-centric data layer that consolidates fragmented sources into a central structure
- Provide strategic guidance on how data should be organized, named, and modeled for long-term sustainability
- Establish best practices for schema versioning, documentation, and change control
- Design and implement the company’s first ETL framework, defining how data is extracted, transformed, and loaded from multiple sources
- Build automated, reliable pipelines that move data from the centralized database and external tools into analytics-ready structures
- Standardize transformation logic to clean, normalize, and enrich data for business use
- Implement pipeline monitoring, error handling, and validation for data quality assurance
- Provide architectural and workflow recommendations for how data should flow between systems and teams
- Define how analysts should access, refresh, and use data safely and consistently
- Partner with the Data & Analytics Manager to align the engineering roadmap with BI and reporting priorities
- Develop scalable, reusable scripts and frameworks that simplify ongoing data management
- Integrate data from internal and third-party platforms into a centralized environment
- Optimize query and pipeline performance for high-volume operations
- Build APIs or microservices for data synchronization and access
- Document data lineage, schema definitions, and system dependencies
- Implement data access controls, validation checks, and compliance standards
- Maintain transparent documentation for analysts, developers, and leadership
- Promote data stewardship and governance best practices across departments
Requirements
- 3–5 years of experience in data engineering, architecture, or backend development
- Proven success building or restructuring data environments for scalability and reliability
- Strong command of SQL and at least one programming language (Python, NodeJS, or similar)
- Experience designing and implementing ETL/ELT frameworks from scratch
- Hands-on experience with data warehouses or data lakes (Azure, Microsoft Fabric, Snowflake, or AWS Redshift)
- Solid understanding of data modeling principles, including star schema and normalization
- Familiarity with APIs, data validation, and version control (Git)
Benefits
- Health insurance
- Professional development opportunities
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
data architectureETL frameworkdata modelingSQLPythonNodeJSdata warehousingdata lakesdata validationversion control
Soft skills
strategic guidancebest practicesdata stewardshipgovernancecollaboration