Senior Data Engineer

Sr. Data Platform EngineerType: Permanent, Full-TimeLocation: Chicago, downtownSchedule: 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 applicationsApply 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 interoperabilityIntegrate metadata standards, lineage tracking, and data quality controls directly into engineering workflowsIdentify and resolve pipeline failures, performance issues, and data anomaliesBuild out observability tools, logging, alerting, and dashboards to maintain end-to-end platform healthRequirements:Bachelor's degree in Computer Science, Engineering, Information Systems, or related field (or equivalent experience)5+ years of data engineering experience in cloud environmentsHands-on expertise with modern data platforms, preferably DatabricksStrong proficiency in Python and SQL, with experience in data transformation frameworksProven experience building ETL/ELT pipelines and orchestration workflows (e.g., Airflow, Databricks Workflows) with CI/CD integrationExposure to AI/ML engineering, feature stores, model monitoring, or MLOps conceptsExperience with infrastructure-as-code tools (Terraform, CloudFormation) or DevOps practices