IT Principal Data Engineering

We are looking for a Principal Data Engineer to sitat the intersection of data engineering and applied data science. Youwillown the design, development, and operation of theplatformsandpipelines that power ourdata science capabilities— ensuringdataflowsreliably fromsourcesystems through to analysis, and business consumption.

This role isroughly
75% data engineering and
25% data science andisidealfor someone whobuildswithengineeringrigor butthinkswithadata sciencemindset; someone who is energized by building platforms that make AI real in an organization. The right candidate is curious by nature — you explore out-of-the-box ideas and stay current with the fast-moving AI/Machine Learning (ML) landscape.

You’ll work directly with business analysts, product owners, business end-users, engineering and application teams, and our own data/platform engineering teams. A consultative communication style is critical as shared outcomes across technology and business are the expectation.

• Define the long-term technical direction for the data science platform and integration with existing ELT pipelines
• Ensure platformsare scalable, reliable, secure, and cost-efficientat enterprise scale
• Evaluate and adoptemerging toolsinthemoderndata and MLstack
• Design, develop, and optimize ETL pipelines and outbound data feeds
• Develop and follow templates and engineering patterns to reduce the time-to-deploy new data assets or changes to an existing data model or analytics solutions
• Partner with key business teams to understand their data needs and assist them in building appropriate data solutions to meet their business needs

• Design, build, and optimize end-to-end data science pipelines— fromraw data ingestion through feature engineering, model training, and inference serving
• Contribute to MLOps practices including model versioning and monitoring, supporting the transition of data science work into production

• Provide technical guidance todataengineers
• Conduct code reviews and championengineering best practices across work streams
• Leadwithoutdirect authority, influencing cross-functional teams acrossdataengineering, analytics and product owners

• Establish best practices for data quality, lineage, privacy, and security across data engineering and science pipelines
• Ensure modelinputsand outputs are auditable, reproducible, and compliant with datagovernancestandards

• Partner with data engineering, product owners, and software engineers to align platformcapabilitieswith organizational AI/ML goals
• Translate complex technical concepts into clear, actionable insights for non-technical stakeholders

• Bachelor’s degree in computer science, engineering, mathematics, or arelated field, OR 7+ years of equivalent verifiable experience, skillset, and record of accomplishment
• Experience in a Principal or Senior Data Engineer role withdirectinvolvementin ML platform orData Science work
• Proficiency in ananalytics/BI tool such as Power BI
• Modern data stack technologies— Databricks(strongly preferred), Snowflake, Spark
• Inbound/outbound transportation of data with APIs and FTPs
• MPPdatabases suchas Databricks, Snowflake, Big Query, Teradata, or Azure Synapse
• Pythonand SQL
• ML& Data Science experience
• Buildinganddeploying ML models(classification, regression, forecasting, NLP, or similar)
• Familiarity with MLframeworkssuchas scikit-learn, XGBoost, PyTorch, or Tensor Flow
• MLfloworsimilar toolsfor experimenttracking, model registry, and deployment
• Understanding of feature engineering, modelevaluation, and common
  
  ML failuremodes
• Strong understanding of data modelling techniques (Kimball, Data Vault) and distributed systems
• Familiarity withfeaturestores, trainingpipelines, and batch/real-time inference architectures

Simplicity (operate) – the drive to identify root cause and innovate to remove complexity to deliver the best outcome

Heart (emotion) – the passion that drives you to get up every day and work hard to strive for excellence

Performance Excellence (mindset) – clearly defining high expectations, driving ownership of key roles and responsibilities, executing with integrity and emphasis while creating a culture of accountability

Respect (philosophy) – taking pride in being inclusive and treating everyone who comes through the doors with respect

• 401K company match up to 4%
• Paid Time Off
• Medical Insurance options including FSA & HSA
• Vision Insurance
• Employee Assistance Programs
• Team Member Referral Program
• Tuition Reimbursement

The above statements are intended to describe the general nature of the work performed by the employees assigned to this job. All employees must comply with Company policy and applicable laws. The responsibilities, duties and skills required of personnel so classified may vary within each department and /or location.