Data Engineer IV

H&P TAX, H&P CONSULTING, INC.
Atlanta, GA, United States
4 days ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours

Tech stack

Artificial Intelligence Airflow Continuous Integration Data Architecture Information Engineering Data Infrastructure Extract Transform Load (ETL) Data Transformation Relational Databases Database Development DevOps Dimensional Modeling
+20 more
Microsoft SQL Server NoSQL Power BI Standard Sql Software Engineering SQL Server Integration Services Data Streaming Workflow Management Systems Enterprise Data Management Cloud Platform System Apache Spark Agentic-AI Git Data Lakes Git Flow Star Schema Data Management Software Version Control Data Pipelines Databricks

Job description

The Data Engineer IV is a modern enterprise data engineering professional responsible for building, optimizing, and maintaining scalable data platforms in a hybrid on-premises and cloud environment. This role supports enterprise analytics, reporting, and AI-driven initiatives using a Lakehouse architecture, with Databricks as the strategic future-state platform.

The ideal candidate combines strong SQL and data modeling expertise with modern Spark-based technologies and familiarity with AI-assisted development tools.

Core Responsibilities

Enterprise Data Engineering

  • Design, build, and maintain batch and/or streaming data pipelines
  • Develop and optimize ETL processes using SSIS or similar tools
  • Work with relational databases, data lakes, and NoSQL systems
  • Normalize and model data using:
  • Star schema
  • Dimensional modeling techniques
  • Transform raw data into curated, reusable datasets

Lakehouse & Modern Data Platforms

  • Develop and support solutions on Spark-based platforms
  • Work with Databricks Lakehouse architecture (primary future-state platform)
  • Support analytics and reporting via Power BI
  • Manage data orchestration workflows (e.g., Airflow or equivalent)
  • Implement CI/CD and Git-based workflows for data pipelines

AI-Assisted & Modern Engineering Practices

  • Leverage AI tools or copilots to assist with:
  • SQL development
  • Pipeline generation
  • Testing
  • Documentation
  • Explore automation or AI agents to streamline engineering workflows

Requirements

  • Strong SQL and data modeling experience
  • Hands-on experience with:
  • SQL Server
  • SSIS (or similar ETL tools)
  • Power BI
  • Experience with Spark-based platforms
  • Working knowledge of Databricks (preferred strategic platform)

Data Engineering Competencies

  • Batch and real-time pipeline development
  • Data quality and validation practices
  • Relational and NoSQL systems
  • Orchestration tools (Airflow or equivalent)
  • CI/CD pipelines
  • Git-based version control

Soft Skills & Work Environment Fit

  • Strong written and verbal communication skills
  • Comfortable collaborating with engineers and managers in:
  • Electric utility
  • Operations-heavy domains
  • Able to operate in regulated, production-critical enterprise environments
  • Analytical, detail-oriented, and solution-focused

Experience Requirements

  • 5+ years in data engineering or related software engineering roles
  • Experience in enterprise environments with hybrid on-prem and cloud systems

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