Role Summary

Are you a senior data engineering leader who thrives on designing scalable, high-performance data platforms that drive real business impact? We are seeking a Principal Data Engineer to lead the architecture, development, and optimization of enterprise data solutions that power analytics, integrations, and data-driven decision making across the organization.

In this role, you’ll serve as a technical authority for cloud-based data platforms, leveraging AWS and Snowflake to build secure, reliable, and cost-effective data ecosystems. You’ll design modern ELT/ETL pipelines, define data modeling and governance standards, and enable seamless data exchange through RESTful and event-driven APIs. Partnering closely with data scientists, analysts, application teams, and business stakeholders, you’ll ensure the data platform aligns with long-term business objectives while supporting both real-time and batch use cases.

This is an exciting opportunity for a hands-on technical leader who enjoys mentoring engineers, shaping architectural direction, and continuously evolving a modern data stack. If you’re passionate about cloud data engineering, platform scalability, and building resilient data solutions in a highly collaborative environment, we’d love to meet you.

Essential Job Duties:

• Architect and maintain enterprise data platforms using AWS services (S3, Glue, Lambda, Redshift, Step Functions, EventBridge) and Snowflake, ensuring high availability, scalability, and performance.
• Design and implement RESTful and event-driven API architectures to enable secure, governed data exchange across internal systems and external partners
• Build and optimize ELT/ETL pipelines for batch and real-time data ingestion, transformation, and delivery using tools such as AWS Glue, dbt, and Snowpipe
• Define and enforce data modeling standards, including dimensional modeling, data vault, and schema design best practices within Snowflake
• Establish and maintain data governance frameworks, including data quality monitoring, lineage tracking, metadata management, and access controls
• Lead cost optimization initiatives across AWS and Snowflake environments, including warehouse sizing, storage strategies, and compute resource management
• Collaborate with data scientists, analysts, and application teams to design data products and self-service analytics capabilities
• Develop and maintain CI/CD pipelines for data infrastructure using Infrastructure as Code (Terraform, CloudFormation) and version control best practices
• Mentor and provide technical leadership to data engineers, conducting architecture reviews and establishing coding standards across the team
• Evaluate and integrate emerging technologies and tools to continuously improve the data platform’s capabilities, reliability, and eDiciency

Qualifications:

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field (Master’s preferred)
• 10+ years of progressive experience in data engineering, data architecture, or a related technical discipline
• 5+ years of hands-on experience designing and building data solutions on AWS (S3, Glue, Lambda, Redshift, Step Functions, IAM)
• 3+ years of experience with Snowfl ake, including performance tuning, data sharing, and administration
• Strong proficiency in SQL, Python, and at least one additional programming language (Java, Scala, or similar)
• Demonstrated experience designing and consuming RESTful APIs, including API gateway management and integration patterns
• Experience with Infrastructure as Code (Terraform or CloudFormation) and CI/CD pipeline development
• Deep understanding of data modeling methodologies (dimensional, data vault, normalized)

What Will Make us LOVE You

• Experience as a technical leader or mentor
• Experience with Apigee API management platform for enterprise API governance, security policies, and developer portal management
• AWS certifications (Solutions Architect Professional, Data Analytics Specialty, or Data Engineer Associate)
• SnowPro Advanced certifications (Data Engineer or Architect)
• Experience with dbt for data transformation and analytics engineering workflows
• Familiarity with data observability and quality tools (Monte Carlo, Great Expectations, or similar)
• Experience with Apache Kafka, Kinesis, or other streaming technologies for real-time data pipelines
• Knowledge of data privacy regulations (HIPAA, GDPR, CCPA) and implementing compliant data architectures
• Experience with containerization (Docker, ECS, EKS) and microservices architectures
• Background in healthcare, fi nancial services, or other highly regulated industries

Are you FIT? Learn more about our Company culture

• Flexible. Vibrant, collaborative & diverse culture that is open-minded & embraces change.
• Insightful. Innovative industry experts who transform client businesses by delivering winning outcomes.
• Trusted. Experienced, reliable & accountable advocates with unwavering integrity.