Principal Engineer Software

Role Overview

The Principal Engineer, Data provides technical leadership across the design, development, modernization, and operation of enterprise data platforms and analytics solutions. This role is responsible for defining scalable data engineering patterns, leading complex data integration and transformation initiatives, and enabling reliable, governed, and high-performing data products that support business reporting, analytics, and advanced AI/ML use cases.

What You Will Do

Provide technical feasibility analysis and solution evaluation for data and analytics initiatives based on business, operational, and regulatory needs. Lead the design and implementation of scalable data engineering solutions, including data pipelines, data models, data integrations, and analytics-ready data products.

Why It Might Be a Fit

Proven experience designing, developing, and maintaining complex data solutions involving multiple systems, stakeholders, business domains, and production dependencies. Strong experience with Python, SQL, distributed data processing, and ETL/ELT development; experience with Spark or similar large-scale data processing frameworks strongly preferred.

Requirements

• Bachelor’s degree in computer science, information systems, data engineering, analytics, engineering, or equivalent training and experience.
• 12+ years of experience in software engineering, data engineering, analytics engineering, or enterprise data platform development.
• Strong experience with Python, SQL, distributed data processing, and ETL/ELT development; experience with Spark or similar large-scale data processing frameworks strongly preferred.
• Experience with cloud-based data platforms and services, preferably AWS, including development, deployment, monitoring, and operational support of data solutions.
• Experience with enterprise data warehouses, data marts, reporting platforms, and business intelligence solutions; familiarity with platforms such as Redshift, Snowflake, SAP BusinessObjects Data Services, SAP Web Intelligence, or similar technologies preferred.
• Experience with modern data transformation and analytics engineering tools such as dbt or equivalent frameworks preferred.
• Strong understanding of data modeling, data warehousing, data quality, metadata management, data lineage, performance optimization, and production support practices.
• Working knowledge of AI/ML concepts and the data engineering practices required to support advanced analytics, machine learning, and model-ready datasets.
• Proven ability to design data solutions that integrate with internal and external systems while meeting security, governance, scalability, and reliability requirements.
• Deep understanding of software development and data engineering practices in a distributed team environment, including version control, testing, CI/CD, release management, and operational monitoring.
• Excellent problem-solving, analytical, communication, and stakeholder management skills.
• Proven team player with the ability to mentor technical team members and influence engineering direction across teams.
• Cloud, data engineering, data architecture, analytics engineering, or AI/ML certifications preferred.

Benefits

• Flexible work environment
• Fluid career paths
• Internal mobility
• Purpose, well-being, and work-life balance
• Welcoming and inclusive environment
• Volunteering opportunities