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# Data Engineer

- **Company:** Baker & McKenzie
- **Location:** Chicago, IL, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Business Analytics Applications, Data Analysis, Microsoft Azure, Software as a Service, Cloud Computing, Information Systems, Databases, Data Cleansing, Information Engineering, Data Governance, Data Integration, Data Transformation, Data Systems, Data Warehousing, Database Queries, Software Debugging, Python (Programming Language), Machine Learning, Microsoft Software, Software Engineering, Transact-SQL, Unstructured Data, Enterprise Data Management, Data Processing, Scripting, Enterprise Software Applications, Snowflake, Apache Spark, Microsoft Fabric, Information Technology, Data Management, Data Pipelines, Databricks
- **Published:** October 29, 2026
- **Apply:** https://www.careerbuilder.com/job-details/data-engineer-chicago-il--72745ff0-bb7e-4ce1-9809-32aa7ad36238

## About the Role

Microsoft Product Family, Data Management, Data Processing, Analysis Skills, Unstructured Data, Software as a Service (SaaS), Application Programming Interface (API), Structured Data, Python Programming/Scripting Language, Microsoft Transact-SQL (T-SQL), * Bachelor's degree in Computer Science, Data Science, Software Engineering, Information Systems, or a related discipline.

 * Five to six years of direct professional experience in data engineering.
 * Strong professional experience developing data solutions using Python.
 * Strong knowledge of T-SQL and experience developing and optimizing complex queries and data transformations.
 * Demonstrated experience designing, building, and maintaining data pipelines.
 * Experience working with structured, semi-structured, and unstructured data.
 * Experience developing data processing solutions using Spark and notebooks.
 * Strong understanding of data integration, data transformation, data quality, and data modelling principles.
 * Experience troubleshooting data pipelines and resolving data processing and performance issues.
 * Strong analytical, debugging, and problem-solving skills.
 * Ability to create clear technical documentation covering processes, solutions, and standards.
 * Ability to collaborate effectively with technical and non-technical stakeholders in a global environment.
 * Strong written and verbal communication skills in English., * Hands-on experience with Microsoft Fabric.
 * Experience with other cloud-based or SaaS data platforms, such as Snowflake or Databricks.
 * Experience working with Microsoft Azure or other major cloud platforms.
 * Familiarity with software development lifecycle practices and delivery methodologies such as Scrum and Kanban.
 * Familiarity with data anonymization and data protection techniques.
 * Experience supporting analytics, business intelligence, artificial intelligence, or machine learning solutions.

## Description

* Design and develop data engineering solutions primarily within Microsoft Fabric.
 * Build, maintain, and optimize scalable data pipelines to ingest, transform, and deliver data from multiple sources.
 * Develop and maintain Spark notebooks for data processing, transformation, and analysis.
 * Work with structured, semi-structured, and unstructured data from databases, APIs, SaaS applications, and other enterprise systems.
 * Develop data transformation processes using Python and T-SQL.
 * Perform data cleansing, validation, aggregation, filtering, and enrichment to ensure data is accurate and fit for purpose.
 * Implement data quality controls and monitoring within data pipelines.
 * Troubleshoot and resolve data processing, integration, and performance issues.
 * Collaborate with data architects, analysts, product owners, and other technology teams to translate requirements into scalable technical solutions.
 * Support the development and maintenance of enterprise data platforms, data warehouses, and analytics solutions.
 * Create and maintain technical documentation for data pipelines, processes, standards, and operating procedures.
 * Follow established software development, data governance, security, and deployment standards.