Senior Data Engineer

About the Role

The day-to-day responsibilities of this role are centered around ensuring the data infrastructure is scalable, reliable, and efficient. This involves designing and extending multi-tenant data architectures, evaluating and improving warehouse design, data models, and schema strategies. The successful candidate will also lead and execute infrastructure migrations with minimal downtime and high data integrity, among other key responsibilities.

Valon Mortgage is committed to innovation and customer-centricity. The company's mission to empower every homeowner by making the mortgage experience simple, secure, and financially empowering requires a cohesive team effort. As a Senior Data Engineer, you will be part of a team that values collaboration, continuous improvement, and customer impact.

What You Will Do

• Own and optimize Valon's core data infrastructure for performance, reliability, and cost efficiency as data volume and complexity grow.
• Design and extend multi-tenant data architectures to support a scalable SaaS model.
• Evaluate and improve warehouse design, data models, and schema strategies to minimize redundancy and maximize query performance.
• Lead and execute infrastructure migrations with minimal downtime and high data integrity.
• Build and maintain custom ingestion pipelines for data sources not covered by ELT vendors.
• Implement observability tooling for pipeline health, latency, data freshness, drift detection, and schema change monitoring.
• Optimize data transformation jobs for speed and cost efficiency, identifying performance bottlenecks and refactoring as needed.
• Establish and run routine maintenance processes to ensure data quality, stability, and platform consistency.
• Drive a culture of data reliability engineering by codifying best practices, automation, and operational excellence.
• Define and communicate the long-term data infrastructure roadmap, aligning technical evolution with Valon's business growth.
• Partner closely with the analytics team to enable faster insights through better tooling, performance, and documentation.
• Act as a force multiplier for the broader data team - mentoring on best practices and improving development velocity across pipelines and models.

What We Are Looking For

• A bachelor's degree in Computer Science, Information Technology, or a related field.
• At least 5 years of experience in data engineering, with a focus on cloud-based data infrastructure and scalability.
• Proficiency in data engineering tools and technologies such as data pipelines, data warehouses, and data lakes.
• Experience with data modeling, data architecture, and database design.
• Strong programming skills in languages such as Python, Java, or Scala.
• Experience with data transformation and processing frameworks like Apache Beam or Spark.
• Knowledge of data governance, data quality, and data security principles.
• Excellent problem-solving skills and the ability to work collaboratively in a team environment.
• Strong communication skills to effectively convey technical ideas to both technical and non-technical stakeholders.

Nice to Have

• Experience with machine learning or artificial intelligence applications in data engineering.
• Familiarity with cloud platforms such as AWS, GCP, or Azure.
• Knowledge of containerization using Docker and orchestration using Kubernetes.
• Experience with agile development methodologies and version control systems like Git.
• Certification in data engineering or a related field.

Benefits and Perks

• Competitive salary and benefits package.
• Opportunity to work with a cutting-edge technology stack and contribute to the development of innovative solutions.
• Collaborative and dynamic work environment with a team of experienced professionals.
• Professional development opportunities, including training, mentorship, and conference attendance.
• Flexible working hours and remote work options to ensure a healthy work-life balance.
• Access to the latest tools and technologies to stay ahead in your career.
• Recognition and reward for outstanding performance and contributions to the company's growth.

• Tip: Ensure your proficiency in Excel is highlighted in your resume and cover letter, as it's a key skill for this role.
• To stand out, showcase projects or experiences where you've successfully optimized data infrastructure or built scalable data pipelines.
• During the interview, be prepared to discuss your approach to data reliability engineering and how you drive a culture of operational excellence.
• Having a portfolio or GitHub repository with examples of your data engineering work can significantly enhance your application.
• When discussing salary, be prepared to talk about your current compensation and what you're expecting based on industry standards and your experience.
• Pay attention to the company culture and values during the interview process; it's crucial to find a good fit for long-term success and satisfaction.