Senior Data Engineer - Analytics chez Carrix, Inc.

Carrix is committed to making our employees feel welcome and respected. Our team is unique and our approach successful because we have fostered an environment that values varying backgrounds, perspectives, and experiences and takes pride in how the collective delivers value to our customers and partners.

A truly diverse workforce is the outcome of treating people right. Each team member is responsible for creating, maintaining, and enhancing our work culture through collaboration and empathy – as culture doesn’t happen without conscious effort. At Carrix, we expect all employees to treat one another with respect and kindness, no exceptions or excuses.

Summary/Objective:

As a Senior Data Engineer, you will design, build, and maintain the pipelines and platforms that power our enterprise-wide analytics and decision-making. You’ll partner with business stakeholders, peers, and senior leaders to deliver trusted, secure, and scalable data products while helping shape the future of our data strategy. In this role, you will influence technical direction, mentor peers, and act as a trusted advisor across the data community. You’ll play a key role in evolving our platform toward predictive and real-time analytics, supporting initiatives in streaming data, ML/AI, and advanced insights. By working with modern tools and cloud-native platforms, you’ll continue to grow your technical expertise while positioning yourself for future opportunities such as Lead Engineer, Data Architect, or Platform Manager. This is a chance to make an immediate impact while building the foundation for Carrix’s long-term data success.

• Design, build, and maintain complex ETL/ELT pipelines and data integration processes.
• Architect and manage enterprise data models and data products using structured data layering approaches (e.g., Medallion architecture).
• Collaborate with analysts, business teams, and leadership to translate requirements into scalable, secure solutions.
• Implement and maintain data governance, metadata management, and lineage tracking.
• Optimize data infrastructure for performance, scalability, and cost efficiency.
• Ensure compliance with privacy, security, and regulatory standards (GDPR, CCPA, HIPAA, as applicable).
• Partner with DevOps teams to implement CI/CD pipelines, version control (Git), and orchestration tools (e.g., Airflow, Prefect).
• Support streaming data, ML/AI initiatives, and advanced analytics use cases.
• Troubleshoot, optimize, and resolve complex production and development issues.
• Promote best practices in data engineering across the enterprise.
• Other duties as assigned.