Data Engineer

Aptean • Alpharetta, GA

9d

About The Position

Aptean is seeking a hands-on Data Engineer to build, test, and maintain scalable data ingestion and transformation pipelines on Microsoft Fabric. The role is execution-focused and centers on delivering high-quality data solutions that support enterprise reporting, analytics, and AI use cases. The successful candidate will bring experience in modern lakehouse environments, a strong sense of ownership, and a willingness to learn.

The Data Engineer will develop and maintain pipelines across the bronze, silver, and gold layers of the medallion architecture using Microsoft Fabric and Azure technologies. Working with senior engineers, analysts, and business stakeholders, the role translates requirements into reliable, scalable data engineering solutions. It calls for hands-on experience with Python, PySpark, and pipeline orchestration, with a focus on data quality, performance optimization, and operational excellence.

Candidates must be authorized to work in the United States without current sponsorship; Aptean is unable to sponsor work authorization at this time.

Requirements

• 3–5 years of experience building data pipelines in production or near-production environments.
• Hands-on experience with Python and PySpark.
• Experience with Azure Data Factory or similar orchestration tools.
• Familiarity with Microsoft Fabric, or strong experience in Azure Synapse or Databricks and willingness to learn Fabric.
• Solid understanding of SQL, data modeling, and performance optimization.
• Knowledge of medallion architecture and Delta Lake concepts.
• Experience implementing data quality checks and basic SCD handling.
• Familiarity with Git, branching, and CI/CD practices such as Azure DevOps or GitHub Actions.
• Strong problem-solving skills, attention to detail, and an ownership mindset.
• Effective communication skills and ability to collaborate with technical and business teams.
• Authorization to work in the United States without current sponsorship.

Nice To Haves

• Exposure to Power BI and semantic data models.
• Understanding of data governance concepts such as schema versioning and access controls.

Responsibilities

• Build and maintain data ingestion pipelines using Microsoft Fabric (Pipelines, Dataflows Gen2, and Notebooks) and Azure Data Factory.
• Develop Python and PySpark notebooks to cleanse, transform, and enrich data across medallion architecture layers.
• Implement Delta Lake patterns, including partitioning, schema evolution, and incremental loads.
• Apply data quality checks, including null handling, duplicate detection, schema validation, and SCD logic.
• Develop reusable, metadata-driven, and parameterized pipeline frameworks.
• Troubleshoot pipeline failures, performance issues, and data discrepancies, and perform root-cause analysis.
• Participate in code reviews, testing, and CI/CD processes using Git-based workflows.
• Support gold-layer datasets and semantic models for Power BI consumption.
• Monitor pipelines and resolve operational issues within defined SLAs; support on-call rotations as needed.
• Maintain technical documentation such as data dictionaries, mappings, and runbooks.
• Collaborate cross-functionally to deliver high-quality data engineering solutions.

Benefits

• Opportunity to work with modern data technologies including Microsoft Fabric and Azure.
• Collaborative environment with experienced data engineering professionals.
• Exposure to enterprise-level data, analytics, and AI initiatives.
• Growth opportunities through hands-on learning and ownership of impactful projects.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed