IT Principal Data Engineering

Purpose

We are looking for a Principal Data Engineer to sit at the intersection of data engineering and applied data science. You will own the design, development, and operation of the platforms and pipelines that power our data science capabilities — ensuring data flows reliably from source systems through to analysis, and business consumption.

This role is roughly 75% data engineering and 25% data science and is ideal for someone who builds with engineering rigor but thinks with a data science mindset; 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.

Responsibilities

Platform Architecture & Strategy

Define the long-term technical direction for the data science platform and integration with existing ELT pipelines

Ensure platforms are scalable, reliable, secure, and cost-efficient at enterprise scale

Evaluate and adopt emerging tools in the modern data and ML stack

Data Engineering Development

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

Data Science Development

Design, build, and optimize end-to-end data science pipelines — from raw 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

Technical Leadership & Mentorship

Provide technical guidance to data engineers

Conduct code reviews and champion engineering best practices across workstreams

Lead without direct authority, influencing cross-functional teams across data engineering, analytics and product owners

Data Governance & Quality

Establish best practices for data quality, lineage, privacy, and security across data engineering and science pipelines

Ensure model inputs and outputs are auditable, reproducible, and compliant with data governance standards

Stakeholder Management

Partner with data engineering, product owners, and software engineers to align platform capabilities with organizational AI/ML goals

Translate complex technical concepts into clear, actionable insights for non-technical stakeholders

About You

Bachelor’s degree in computer science, engineering, mathematics, or a related field, OR 7+ years of equivalent verifiable experience, skillset, and record of accomplishment

Experience in a Principal or Senior Data Engineer role with direct involvement in ML platform or Data Science work

Proficiency in an analytics/BI tool such as Power BI

Data Engineering experience:

Modern data stack technologies — Databricks (strongly preferred), Snowflake, Spark

Inbound/outbound transportation of data with APIs and FTPs

MPP databases such as Databricks, Snowflake, BigQuery, Teradata, or Azure Synapse

Cloud platforms — AWS, Azure, or GCP

Python and SQL

ML & Data Science experience

Building and deploying ML models (classification, regression, forecasting, NLP, or similar)

Familiarity with ML frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow

MLflow or similar tools for experiment tracking, model registry, and deployment

Understanding of feature engineering, model evaluation, and common ML failure modes

Architecture experience

Strong understanding of data modelling techniques (Kimball, Data Vault) and distributed systems

Familiarity with feature stores, training pipelines, and batch/real-time inference architectures

Our Values 

Ability to demonstrate, understand and apply our workplace values. 

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  

Benefits 

401K company match up to 4%

Paid Time Off 

Medical Insurance options including FSA & HSA

Vision Insurance

Dental insurance

Employee Assistance Programs

Team Member Referral Program

Tuition Reimbursement

Wellbeing Program

Career development opportunities

 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.