Senior Data Engineer — Cloud Data & AI Solutions

Concurrency, Inc.

Town of Brookfield (WI)

On-site

USD 110,000 - 140,000

Full time

9 days ago

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Job summary

Concurrency, Inc. in Wisconsin is seeking a Data Engineer to join our Cloud, Data & AI Solutions Team.

You will design, build, and optimize scalable data solutions using Microsoft Fabric, Azure, and modern cloud data platform technologies. You will collaborate with business and technical stakeholders to translate requirements into technical designs, data models, and implementation plans, while developing Fabric Data Factory pipelines and lakehouse architectures to improve data quality and

Qualifications

Over 2 years of experience designing and delivering modern data solutions on Microsoft Azure and/or Microsoft Fabric.
Experience developing and supporting Microsoft Fabric workloads including Data Factory, Lakehouse, Warehouse, Notebooks, or Real-Time Analytics.
Understanding of Medallion Architecture (Bronze, Silver, Gold) and modern data engineering best practices.
Experience building ELT/ETL pipelines using SQL, Python, PySpark, Data Factory, or similar cloud-native technologies.
Strong SQL development skills, including stored procedures, data transformation logic, and performance optimization.
Knowledge of dimensional modeling, star schemas, Data Vault, and other analytical data modeling techniques.
Ability to gather business requirements and translate them into source‑to‑target mappings, data models, and technical solutions.
Experience developing semantic models, reports, and dashboards using Power BI.
Understanding of data governance, data quality, security, and performance considerations within cloud data platforms.

Responsibilities

Design, build, and optimize scalable data solutions using Microsoft Fabric, Azure, and modern cloud data platform technologies.
Partner with business and technical stakeholders to gather requirements and translate them into technical designs, data models, and implementation plans.
Develop and maintain Fabric Data Factory pipelines, dataflows, notebooks, and orchestration processes for reliable data ingestion and transformation.
Build and support Lakehouse architectures leveraging Bronze, Silver, and Gold (Medallion) layers to improve data quality, governance, and analytics readiness.
Develop ELT/ETL solutions using SQL, PySpark, Python, and Fabric notebooks to transform and enrich enterprise data.
Create and optimize data models that support reporting, self-service analytics, AI, and machine learning initiatives.
Support migrations from legacy data platforms, on‑premises databases, and third‑party systems into Microsoft Fabric and Azure data services.
Implement data quality, monitoring, security, and governance practices that align with enterprise standards.