This role exists to build the technical backbone that finally unifies our data. The Data Engineer will establish the structures, standards, and pipelines that turn scattered information into a trusted, governed, and scalable ecosystem. By creating proper schemas, mapping logic, and automated ETL processes, this role ensures that every team, from Operations to Finance to Analytics, can work with accurate, dependable data.
We’re looking for a builder: someone technical, meticulous, and systems‑driven who can architect a long‑term foundation for how data flows, transforms, and supports our business decisions.
Data Architecture & Schema Design
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.
ETL / ELT Development
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 (ClickCRM, Twilio, LeadLoop, Finance, etc.) 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.
Workflow Optimization & Advisory
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.
Integration & Performance Optimization
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.
Collaborate with DevOps to ensure infrastructure stability, backup policies, and monitoring.
Governance, Security, & Documentation
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.
A systems thinker who enjoys building from the ground up.
Comfortable making architectural decisions that balance long-term scalability with immediate needs.
Detail-oriented, reliable, and committed to producing high-integrity data structures.
Able to partner well with both technical teams and business stakeholders.
Calm, clear, and collaborative, even when juggling competing priorities.
Required Qualifications
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).
Experience with Clickhouse, Redis, or Cassandra.
Familiarity with BI tools like Power BI, Looker, or Tableau.
Experience with orchestration tools (Airflow, Docker, Kubernetes).
Strong documentation habits and systems-thinking skills.
Ability to translate technical concepts into clear recommendations.
Location: Remote
Department: Data & Analytics
Reports To: CEO
Note: During onboarding and probation, this role will work under the guidance of the current Data / Product Manager (interim supervisor).
Employment Type: Full-Time