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Data Engineer
Data EngineerRagle Inc • North Richland Hills, TX, United States
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Data Engineer

Data Engineer

Ragle Inc • North Richland Hills, TX, United States
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  • [job_card.full_time]
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Data Engineer (2-3 Years Experience)

Location : North Richland Hills, TX (On-site)

Salary Range : $90,000–$110,000 (based on experience)

Company : Ragle Inc.

Reports to : Data & Analytics Lead

About the Role

Ragle Inc. is expanding its Data & Analytics team and is seeking a hands-on Data Engineer with 2–3 years of industry experience to help centralize and modernize operational, accounting, and project data.

In this role, you will design and operate production-grade data pipelines that connect our in-house platform, accounting systems, telematics, scheduling, estimating tools, Smartsheet, and third-party APIs. These pipelines will power analytics used daily by Operations, Accounting, Estimating, and Executive Leadership .

What You’ll Do

  • Design, build, and maintain reliable data pipelines using SQL and Python
  • Ingest data from Azure SQL databases , third-party APIs, and structured file sources (CSV / Excel)
  • Help establish and maintain a centralized analytics data model (fact and dimension tables)
  • Partner with analysts to support Power BI semantic models and improve dataset performance
  • Implement data quality checks, logging, monitoring, and alerting
  • Collaborate with business stakeholders to translate workflows into robust data products
  • Contribute to version control, deployment, and data engineering standards (Git, environments)
  • Support migrations away from manual Excel workflows toward automated, governed datasets

Key Responsibilities

  • Build ETL / ELT processes integrating operational, accounting / payroll, and fleet telematics data
  • Optimize SQL queries, views, and table structures for analytics performance and incremental loads
  • Maintain documentation for pipelines, datasets, schemas, and data contracts
  • Assist with access control, governance, and data security best practices
  • Troubleshoot refresh failures and performance bottlenecks across the data stack
  • Required Qualifications

  • 2–3 years of professional experience as a Data Engineer or Analytics Engineer
  • Strong SQL skills (complex joins, CTEs, window functions, performance tuning)
  • Hands-on Python experience for data processing (pandas, standard libraries)
  • Experience with relational databases (SQL Server / Azure SQL, Postgres, or similar)
  • Experience building and maintaining production data pipelines
  • Understanding of data modeling concepts (star schema, keys, SCD basics)
  • Familiarity with Power BI or similar BI tools
  • Comfortable working directly with business stakeholders
  • Preferred Qualifications

  • Azure experience (Azure SQL, Data Factory, or Fabric Data Pipelines)
  • REST API ingestion experience
  • ERP or operational systems integration exposure
  • Git-based workflows and basic CI / CD
  • Construction or asset-heavy industry experience
  • Desire to grow into Senior Data Engineer or Analytics Lead roles
  • What Success Looks Like

  • Stable, documented, and trusted data pipelines
  • Reusable datasets replacing manual Excel workflows
  • Analytics relied upon for daily decision-making
  • Smooth onboarding of new systems and data sources
  • A scalable data platform supporting company growth
  • Why Join Ragle Inc.

  • Real operational data with direct business impact
  • High ownership and production responsibility
  • Small team with leadership visibility
  • Professional development and certification support
  • Compensation & Benefits

    Competitive salary ( $90,000–$110,000 based on experience), plus health, dental, and vision insurance , paid time off and holidays , and professional development support .

    Additional Information

    Ragle Inc. conducts professional reference checks as part of our standard hiring process.

    Ragle Inc. is an Equal Opportunity Employer . We are committed to creating a diverse and inclusive workplace and make employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other protected status in accordance with applicable laws.

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