Mining engineer Jobs in Chicago, IL

MalaceHR is seeking an experienced Data Engineer to join a fast-paced technology and enterprise data environment. This position will be responsible for designing, developing, and optimizing scalable data solutions using modern cloud and big data technologies.

The ideal candidate is a self-starter with strong hands-on experience in Azure Databricks, Python, PySpark, Spark SQL, Azure Functions, Delta Lake, Azure DevOps CI/CD, and agent-driven workflows leveraging MCP frameworks. This individual will work closely with cross-functional technical and business teams to develop data pipelines, modernize data platforms, and support enterprise-level data initiatives.

Key Responsibilities

• Design, architect, and develop scalable data solutions using cloud-based big data technologies.
• Ingest, process, transform, and analyze large and diverse datasets to support business and technical requirements.
• Design and develop data management and persistence solutions using relational and non-relational databases.
• Build scalable data lake solutions capable of storing structured, semi-structured, and unstructured data from internal and external sources.
• Develop proofs of concept (POCs) to validate new technologies, architectures, and solution proposals.
• Provide technical guidance supporting migrations to modern cloud-based data platforms.
• Develop, maintain, and optimize ETL and ELT workflows using Azure Databricks, Python, PySpark, and Spark SQL.
• Extract, manipulate, and transform data from databases, data lakes, APIs, files, streaming platforms, and other data sources.
• Develop efficient data-processing pipelines with appropriate validation, error handling, monitoring, and performance tuning.
• Build systems that ingest, cleanse, normalize, and structure large and diverse datasets.
• Develop event-driven and streaming data pipelines supporting real-time and near-real-time processing.
• Contribute to and follow CI/CD processes and Data Engineering development best practices.
• Perform unit testing, system integration testing, regression testing, and support user acceptance testing.
• Translate business requirements into scalable technical solutions that can be designed and engineered.
• Partner with business stakeholders to develop technical documentation and communication materials supporting proper data usage and interpretation.
• Implement data security best practices, including encryption, access controls, data governance, and compliance requirements.
• Maintain data privacy, confidentiality, quality, and integrity throughout the data engineering lifecycle.
• Perform data analysis and troubleshooting to identify and resolve data-related issues.
• Build agent-driven workflows used to load, process, and transform data.
• Develop data solutions leveraging MCP frameworks and agent orchestration.
• Collaborate with software engineers, architects, product teams, analysts, and other cross-functional stakeholders.

Qualifications

• Minimum of 5 years of professional Data Engineering or Data Development experience.
• Strong hands-on experience with:
  • Python
  • PySpark
  • Spark SQL
  • ETL/ELT development
  • SQL Server
  • Data pipeline development
• Bachelor’s degree in Computer Science, Information Science, Mathematics, Statistics, Engineering, Data Science, or another related quantitative discipline preferred.
• Experience working with Microsoft Azure cloud technologies.
• Strong experience with Azure Databricks and Azure Storage/Data Lake technologies.
• Strong understanding of data engineering architecture, data modeling, data integration, and ETL concepts.
• Excellent analytical, technical, troubleshooting, and organizational skills.
• Strong written and verbal communication skills, including technical documentation.

Technical Skills & Competencies

• Hands-on experience working with structured, semi-structured, and unstructured data.
• Experience developing solutions within data lake environments.
• Experience building event-driven data pipelines utilizing queues, streaming platforms, or similar technologies.
• Strong understanding of real-time and near-real-time data processing.
• Advanced hands-on experience with PySpark, Databricks, and Spark SQL.
• Experience working with file and serialization formats including:
  • JSON
  • Parquet
  • CSV
  • Other structured and semi-structured data formats
• Knowledge of NoSQL database technologies such as:
  • Cosmos DB
  • MongoDB
  • HBase
  • Similar distributed database platforms
• Experience with cloud environments such as Microsoft Azure or AWS, with Azure preferred.
• Experience with technologies including:
  • Azure SQL Server
  • Azure Data Lake Storage
  • Azure Event Hubs
  • Azure Functions
  • Azure Search
  • Cosmos DB
  • MongoDB
  • Spark Streaming
  • Delta Lake
  • Azure DevOps
  • CI/CD pipelines
• Experience developing or working with AI agent orchestration and MCP-based workflows is highly desirable.
• Ability to troubleshoot complex data-processing and pipeline performance issues.
• Ability to manage multiple projects and priorities simultaneously in a fast-paced environment.
• Reliable, self-motivated, organized, and capable of working independently.
• Strong team player with the ability to collaborate effectively with cross-functional technical and business teams.