Senior Data Engineer

Sr. Data Platform Engineer

Type: Permanent, Full-Time

Location: Chicago, downtown

Schedule: HYBRID; 3 days onsite (non negotiable)

Overview:

A senior-level engineering position responsible for building and sustaining the enterprise data platform, enabling analytics, AI/ML capabilities, and responsible data use.

Responsibilities:

• Design, build, and maintain scalable pipelines and ETL/ELT workflows for analytics, reporting, and AI/ML applications
• Apply best practices for data ingestion, transformation, modeling, and orchestration within a modern lakehouse stack (Databricks, Delta Lake, Azure Data Lake)
• Develop high-quality, reusable data models and curated datasets with a focus on usability and interoperability
• Integrate metadata standards, lineage tracking, and data quality controls directly into engineering workflows
• Identify and resolve pipeline failures, performance issues, and data anomalies
• Build out observability tools, logging, alerting, and dashboards to maintain end-to-end platform health

Requirements:

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field (or equivalent experience)
• 5+ years of data engineering experience in cloud environments
• Hands-on expertise with modern data platforms, preferably Databricks
• Strong proficiency in Python and SQL, with experience in data transformation frameworks
• Proven experience building ETL/ELT pipelines and orchestration workflows (e.g., Airflow, Databricks Workflows) with CI/CD integration
• Exposure to AI/ML engineering, feature stores, model monitoring, or MLOps concepts
• Experience with infrastructure-as-code tools (Terraform, CloudFormation) or DevOps practices