Data Engineer

Description

We are looking for a Data Engineer to join a real estate and property organization in Chicago, Illinois on a contract-to-permanent basis. This role is ideal for a hands-on builder who can create and improve modern data pipelines, manage core data platforms, and support reliable data delivery across the business. You will work within the Azure ecosystem to develop scalable solutions that connect multiple data sources, strengthen data quality, and enable informed decision-making.

Responsibilities:
Design, build, and enhance end-to-end data pipelines using Microsoft Fabric and/or Azure Data Factory for production use.
Manage and improve the data environment with a strong ownership mindset, ensuring performance, reliability, and maintainability.
Integrate data from varied sources such as APIs, databases, and flat files into structured, usable datasets.
Develop data models and schema designs that support reporting, analytics, and downstream business needs.
Monitor data quality and implement validation checks, troubleshooting issues through root cause analysis and continuous optimization.
Create scalable cloud-based data solutions within Azure that support long-term operational and analytical goals.
Partner with cross-functional stakeholders to translate business questions into practical data engineering solutions.
Contribute to orchestration, automation, and ongoing support of data workflows using modern engineering tools and programming languages.

Requirements

Strong hands-on experience with Microsoft Fabric and/or Azure Data Factory, including building and optimizing pipelines.
Proven background working with Azure data services and cloud-based data architecture.
Advanced experience with data modeling, complex querying, and performance tuning in enterprise data platforms.
Solid programming skills in Python, Java, Scala, or a comparable language used in data engineering.
Experience with ETL development, relational databases, and data warehousing concepts.
Familiarity with technologies such as Apache Spark, Hadoop, or Kafka in support of large-scale data processing.
Ability to work effectively as an individual contributor in a lean team environment with high accountability.
Exposure to Power BI or Tableau, along with the ability to align technical solutions with business needs.

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