Data Engineer

APTEAN; Atlanta (GA); On-site; USD 110,000 - 150,000; Full time

Benefits offered by this job

Modern data tech stack

Collaborative environment

Learning opportunities

Job summary

APTEAN is seeking a hands-on Data Engineer to build, test, and maintain scalable data ingestion and transformation pipelines on Microsoft Fabric and Azure. This role centers on delivering high-quality data solutions for enterprise reporting, analytics, and AI use cases.

You will work with Python, PySpark, and Delta Lake patterns across bronze, silver, and gold layers, collaborating with analysts and stakeholders to translate requirements into reliable data engineering workloads.

Qualifications

• 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/Databricks with 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 (Azure DevOps or GitHub Actions).
• Exposure to Power BI and semantic data models is a plus.
• Understanding of data governance concepts such as schema versioning and access controls preferred.

Responsibilities

• Build and maintain data ingestion pipelines using Microsoft Fabric (Pipelines, Dataflows Gen2, 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 handling, duplicate detection, schema validation, and SCD logic.
• Develop reusable, metadata-driven, and parameterized pipeline frameworks.
• Troubleshoot pipeline failures, performance issues, and data discrepancies; 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.

Skills

Python

PySpark

SQL

Data Modeling

Delta Lake

Git

CI/CD

Power BI

Microsoft Fabric

Azure Data Factory

Tools

Azure Data Factory

Microsoft Fabric

Job description

APTEAN

Position Title: Data Engineer

Location: Atlanta GA USA Alpharetta, Georgia US

Location Details: Onsite

Experience Level: B

Country: US

Type: Employee Regular Full Time

Job Description

Overview

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

Are you ready for what’s next, now?

Role Overview

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

About the Role

As a Data Engineer, you will be responsible for developing and maintaining data pipelines across the medallion architecture (bronze, silver, gold) using Microsoft Fabric and Azure technologies. You’ll work closely with senior engineers, analysts, and business stakeholders to translate requirements into reliable, scalable data engineering solutions. This role requires strong hands‑on experience with Python, PySpark, and data pipeline orchestration tools, as well as a focus on data quality, performance optimization, and operational excellence.

Key Responsibilities

• Build and maintain data ingestion pipelines using Microsoft Fabric (Pipelines, Dataflows Gen2, 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 handling, duplicate detection, schema validation, and SCD logic
• Develop reusable, metadata-driven, and parameterized pipeline frameworks
• Troubleshoot pipeline failures, performance issues, and data discrepancies; 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

About You

• 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/Databricks with 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 (Azure DevOps or GitHub Actions)
• Exposure to Power BI and semantic data models is a plus
• Understanding of data governance concepts such as schema versioning and access controls preferred
• Strong problem‑solving skills, attention to detail, and ownership mindset
• Effective communication skills and ability to collaborate with technical and business teams

What’s in It for You

• 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

About Aptean

At Aptean, our mission is to solve tomorrow’s unique challenges today with unrivaled, purpose‑built software and superior customer experiences from people who care.

Aptean is a global provider of mission‑critical, industry‑specific software solutions.

Aptean’ s purpose‑built ERP and supply chain management solutions help address the unique challenges facing process and discrete manufacturers, distributors and other focused organizations.

Aptean’ s compliance solutions are built for companies serving specific markets such as finance, healthcare, biotech and pharmaceuticals, over10,000 highly specialized organizations in more than 20 industries and 80 countries rely on Aptean to streamline their everyday operations.

“At Aptean, our global and diverse employee base is our greatest asset. It is through embracing and understanding our differences that we are able to harness our individual power to maximize the success of our customers, our employees and our company.” – TVN Reddy

Aptean pledges to promote a company culture where diversity, equity and inclusion are central. We are committed to applying this principle as we interact with our customers, build our teams, cultivate our leaders and shape a company in which any employee can succeed, regardless of race, color, sex, national origin, sexuality and gender identity, religion, disability or age. Celebrating our diverse experiences, opinions and beliefs allows us to embrace what makes us unique and to use this as an asset in bringing innovative solutions to our customer base.

Equal employment opportunity, including veterans and individuals with disabilities.

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