Senior Data Engineer (Charlotte)

Role Title : Senior Data Engineer

Client : Global construction and development company

Employment Type : Contract

Duration : 1 year

Preferred Location : Remote based in ET or CT time zones

Role Description :

The Senior Data Engineer will play a pivotal role in designing, architecting, and optimizing cloud-native data integration and Lakehouse solutions on Azure, with a strong emphasis on Microsoft Fabric adoption, PySpark / Spark-based transformations, and orchestrated pipelines. This role will lead end-to-end data engineeringfrom ingestion through APIs and Azure services to curated Lakehouse / warehouse layerswhile ensuring scalable, secure, well-governed, and well-documented data products. The ideal candidate is hands-on in delivery and also brings data architecture knowledge to help shape patterns, standards, and solution designs.

Key Responsibilities

• Design and implement end-to-end data pipelines and ELT / ETL workflows using Azure Data Factory (ADF), Synapse, and Microsoft Fabric.
• Build and optimize PySpark / Spark transformations for large-scale processing, applying best practices for performance tuning (partitioning, joins, file sizing, incremental loads).
• Develop and maintain API-heavy ingestion patterns, including REST / SOAP integrations, authentication / authorization handling, throttling, retries, and robust error handling.
• Architect scalable ingestion, transformation, and serving solutions using Azure Data Lake / OneLake, Lakehouse patterns (Bronze / Silver / Gold), and data warehouse modeling practices.
• Implement monitoring, logging, alerting, and operational runbooks for production pipelines; support incident triage and root-cause analysis.
• Apply governance and security practices across the lifecycle, including access controls, data quality checks, lineage, and compliance requirements.
• Write complex SQL, develop data models, and enable downstream consumption through analytics tools and curated datasets.
• Drive engineering standards : reusable patterns, code reviews, documentation, source control, and CI / CD practices.

Requirements :

• Bachelor's degree (or equivalent experience) in Computer Science, Engineering, or a related field.
• 5+ years of experience in data engineering with strong focus on Azure Cloud.
• Strong experience with Azure Data Factory pipelines, orchestration patterns, parameterization, and production support.
• Strong hands-on experience with Synapse (pipelines, SQL pools and / or Spark), and modern cloud data platform patterns.
• Advanced PySpark / Spark experience for complex transformations and performance optimization.
• Heavy experience with API-based integrations (building ingestion frameworks, handling auth, pagination, retries, rate limits, and resiliency).
• Strong knowledge of SQL and data warehousing concepts (dimensional modeling, incremental processing, data quality validation).
• Strong understanding of cloud data architectures including Data Lake, Lakehouse, and Data Warehouse patterns.

Preferred Skills

• Experience with Microsoft Fabric (Lakehouse / Warehouse / OneLake, Pipelines, Dataflows Gen2, notebooks).
• Architecture experience (formal or informal), such as contributing to solution designs, reference architectures, integration standards, and platform governance.
• Experience with DevOps / CI-CD for data engineering using Azure DevOps or GitHub (deployment patterns, code promotion, testing).
• Experience with Power BI and semantic model considerations for Lakehouse / warehouse-backed reporting.
• Familiarity with data catalog / governance tooling (e.g., Microsoft Purview).