84.51˚ · 6 days ago
Senior ML Data Engineer (P508)
Chicago, IL
Full-time
Onsite
Mid, Senior Level
$97K/yr - $167K/yr
3+ years exp84.51° is a retail data science, insights and media company that helps create personalized experiences for shoppers. They are seeking a Senior ML Data Engineer to architect, build, and operate critical data infrastructure for machine learning models, ensuring production-grade reliability and scalability.
Management Consulting
Responsibilities
Feature Store Operations & Governance (40)
Own the feature request lifecycle from intake through deployment, driving reusability and maintaining a searchable feature catalog
Design and build scalable feature pipelines that compute features from diverse sources (BigQuery, Azure Data Lake) and write to Feature Store infrastructure (Vertex AI Feature Store + BigQuery)
Build streaming feature engineering pipelines using Apache Beam/Dataflow for real time feature computation and low-latency model serving with sub-second data freshness
Ensure point-in-time correctness and online/offline feature consistency to prevent data leakage
Implement drift detection, data quality monitoring, and alerting mechanisms
Develop self-service tools and templates that enable teams to independently create features
Training & Evaluation Data Pipelines (30)
Build automated pipelines that generate ML-ready training datasets by combining features with labeled target variables
Implement point-in-time correctness logic and sophisticated sampling strategies to ensure balanced, representative datasets
Maintain comprehensive dataset versioning for full traceability across model versions
Generate detailed evaluation reports with performance metrics segmented by business dimensions
Support operations across both Azure and Vertex AI environments during platform migration
ML Data Operations & Reliability (20)
Serve as Tier 2/3 on-call responder for feature data quality incidents, diagnosing and resolving pipeline failures and performance issues
Maintain comprehensive lineage tracking and metadata management for full data traceability
Support regulatory compliance through proper data governance and documentation
Standards, Education & Collaboration (10)
Establish and enforce feature naming conventions, data quality thresholds, and point-in-time correctness patterns
Conduct workshops on feature engineering best practices and provide expert guidance on feature design
Partner with Data Scientists, ML Engineers, Data Engineering, and MLOps teams to optimize infrastructure and align with technical strategy
Qualification
Required
3+ years of hands-on experience building and maintaining ML data pipelines in production environments with demonstrated expertise in scaling and reliability
Expert-level SQL skills and advanced Python programming capabilities with experience in data processing frameworks and ML libraries
Proven experience with cloud data platforms, with strong preference for GCP ecosystem including BigQuery, Dataflow, Vertex AI Feature Store, and associated ML services
Deep understanding of end-to-end ML workflows including training data preparation, model evaluation methodologies, and serving infrastructure requirements
Production operations mindset with experience in monitoring, alerting, on-call responsibilities, and meeting SLA commitments
Preferred
Hands-on experience with Feature Store platforms such as Vertex AI Feature Store, Feast, Tecton, or similar enterprise solutions
Deep knowledge of point-in-time correctness principles, temporal joins, and time-series data modeling best practices
Multi-cloud experience with both Azure and GCP platforms, including data migration and hybrid cloud architectures
Strong familiarity with core ML concepts including feature engineering, label creation, train/test/validation splits, and data leakage prevention
Background spanning both analytics engineering and ML-specific data engineering with understanding of the unique requirements of each domain
Benefits
Health: Medical: with competitive plan designs and support for self-care, wellness and mental health. Dental: with in-network and out-of-network benefit. Vision: with in-network and out-of-network benefit.
Wealth: 401(k) with Roth option and matching contribution. Health Savings Account with matching contribution (requires participation in qualifying medical plan). AD&D and supplemental insurance options to help ensure additional protection for you.
Happiness: Paid time off with flexibility to meet your life needs, including 5 weeks of vacation time, 7 health and wellness days, 3 floating holidays, as well as 6 company-paid holidays per year. Paid leave for maternity, paternity and family care instances.
Company
84.51˚
84.51° helps companies create sustainable growth by putting the customer at the center of everything.
1001-5000 employees
H1B Sponsorship
84.51˚ has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (18)
2024 (23)
2023 (29)
2022 (39)
2021 (26)
2020 (17)
Funding
Current Stage
Late StageLeadership Team
Mario DiMercurio
Director, Product - Platform Components
Company data provided by crunchbase