Principal Engineer Data Engineering

Role Description

As a Senior Data Leader, you will design, build, and optimize our enterprise data architecture to drive strategic insights and high-impact business decisions. You will lead the development of end-to-end data pipelines, manage cloud-based data warehouses, and integrate modern DevOps and automated workflows into our data ecosystem.

• Designing and building scalable, high-performance ETL/ELT data pipelines from diverse source systems to cloud platforms.
• Architecting robust data models (conceptual, logical, physical) that support reporting, analytics, and advanced business applications.
• Managing and modernizing enterprise data storage, driving seamless performance across legacy data warehouses (such as Teradata) and modern cloud platforms.
• Implementing DevOps and CI/CD best practices for data pipelines to ensure continuous, automated, and reliable data delivery.
• Optimizing SQL queries, Python scripts, and orchestration workflows to improve system throughput and decrease processing latency.
• Evaluating and integrating innovative data technologies, including AI/ML automation and advanced orchestration tools, into our data infrastructure.

Qualifications

• Bachelor’s degree or four or more years of work experience.
• Six or more years of relevant experience required, demonstrated through one or a combination of work and/or military experience, or specialized training.
• Five or more years of hands-on experience in ETL/ELT data pipeline development.
• Demonstrated experience in Data Modeling, Data Warehousing, and System Architecture.
• Expert-level proficiency in SQL and Python.
• Hands-on expertise with cloud platforms (AWS and/or GCP).

Requirements

• A degree in Computer Science, Data Engineering, Information Systems, or a related technical field.
• Experience with workflow orchestration and integration tools such as Apache Airflow and Talend.
• Strong familiarity with traditional data warehouse platforms like Teradata.
• Proven background implementing DevOps practices for data (DataOps) using Git, Jenkins, and automated testing frameworks.
• Experience leveraging AI/ML tools or generative AI techniques within data engineering workflows (e.g., automated data quality checks, smart ingestion, or AI-assisted code generation).
• Cloud or Data Engineering certifications (e.g., AWS Certified Data Engineer, GCP Professional Data Engineer).

Benefits

• Health and wellness benefit options including medical, dental, vision, short and long term disability, basic life insurance, supplemental life insurance, AD&D insurance, identity theft protection, pet insurance, and group home & auto insurance.
• Matched 401(k) savings plan.
• Up to 8 company paid holidays per year and up to 6 personal days per year.
• Paid parental leave and adoption assistance.
• Tuition assistance and other incentives.
• Newly hired employees receive up to 15 days of vacation per year, which grows with additional service.
• Compensation in the form of premium pay such as overtime, shift differential, holiday pay, allowances, etc.