Data Engineer: Build Scalable Lakehouse Pipelines in Azure

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 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.