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Data Engineers

Role overview

Qualifications

  • 3+ years of experience in Data Engineering or Analytics Engineering
  • Strong SQL expertise for analytical workloads
  • Experience with cloud data warehouses such as BigQuery, Amazon Redshift, Snowflake, or similar platforms
  • Proven experience designing star-schema or dimensional data models

Responsibilities

  • Design, build, and maintain BigQuery datamarts and analytical tables for BI reporting
  • Develop scalable data models, including star schema, snowflake, and denormalized models
  • Build and maintain data pipelines for data ingestion, transformation, and loading into analytics environments
  • Collaborate with BI teams to ensure datasets align with semantic models and dashboards

Key facts

Hard skills

Other skills

  • Collaboration
  • Problem Solving

About the company

VIZX International logo

VIZX International

Outsourcing & Offshoring

VizX Global is the embedded operations partner behind healthcare’s fastest-growing agencies. We help home care agencies, home health organizations, and healthcare staffing firms scale without adding headcount by taking ownership of the operational functions that drive growth. Our teams manage recruiting, scheduling, care coordination, billing, payroll, compliance, and 24/7 support, allowing agency owners to focus on expansion instead of operational bottlenecks. Unlike traditional outsourcing firms, we don’t provide temporary staffing or virtual assistants. We build dedicated healthcare operations teams, manage them entirely, and stay accountable for outcomes. 100+ agencies served. 35% average cost reduction. 40% improvement in caregiver retention. Zero implementation failures. Grow. Run. Protect.

Company details

IndustryOutsourcing & Offshoring
Company size51 - 200

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Job description

 Data Engineer

Job Overview

We are looking for a skilled Data Engineer to design, optimize, and maintain the data architecture that powers our BI environment.

This role focuses on building scalable BigQuery datamarts, optimizing data models, and ensuring reliable data pipelines to support analytics and reporting.

The ideal candidate has strong experience in cloud data warehousing, data modeling, and building analytics-ready datasets that enable efficient BI consumption.

Key Responsibilities

1. Data Architecture & Engineering

  • Design, build, and maintain BigQuery datamarts and analytical tables for BI reporting.
  • Develop scalable data models, including star schema, snowflake, and denormalized models.
  • Optimize query performance and storage efficiency within cloud data warehouses.
  • Collaborate with BI teams to ensure datasets align with semantic models and dashboards.

2. Data Pipeline & Transformation

  • Build and maintain data pipelines for data ingestion, transformation, and loading into analytics environments.
  • Implement transformation workflows using SQL or frameworks such as dbt.
  • Ensure data quality, validation, and consistency across datasets.

3. Data Governance & Performance

  • Maintain data standards, naming conventions, and proper documentation.
  • Implement governance practices, including schema management and version control.
  • Monitor and troubleshoot pipeline failures and data inconsistencies.

4. Collaboration with BI Teams

  • Work closely with BI specialists to ensure datasets support semantic-layer requirements.
  • Deliver optimized datasets that minimize the need for heavy transformations within BI tools.

Required Qualifications

  • 3+ years of experience in Data Engineering or Analytics Engineering.
  • Strong SQL expertise for analytical workloads.
  • Experience with cloud data warehouses such as:
    • BigQuery
    • Amazon Redshift
    • Snowflake
    • Similar platforms
  • Proven experience designing star-schema or dimensional data models.
  • Experience building analytics-ready datamarts.

Preferred Qualifications

  • Experience with dbt or similar data-transformation frameworks.
  • Familiarity with Git-based workflows and CI/CD for data pipelines.
  • Experience with BI tools such as:
    • Looker
    • Tableau
    • Power BI
  • Background working with retail or multi-location data environments.

Key Skills

  • SQL
  • Prompt Engineering
  • Data Engineering
  • Analytics Engineering
  • BigQuery
  • Data Modeling
  • Data Warehousing
  • Data Pipelines
  • BI & Analytics
  • dbt
  • Git / CI/CD

Compensation: Up to $17/hr

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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