Senior Data Services Engineer

Overview:

We are a leading Mortgage Servicing, SaaS-based company that thrives on innovation and excellence. We are currently seeking an experienced Senior Data Services Engineer to design, build, and optimize the data solutions that power our Mortgage Servicing platform. This individual will serve as a technical expert in data engineering, applying strong programming, cloud, and database skills to solve complex business problems and enable data-driven decision making across the organization.

The ideal candidate combines strong software engineering fundamentals with deep expertise in Python, cloud platforms, and database technologies, and brings an understanding of Mortgage Servicing or Financial Services to help ensure technical solutions align with real business and regulatory needs.

Your day-to-day at Sagent:

Data Engineering and Development:

• Design, build, and maintain scalable data pipelines and services using Python and modern data engineering frameworks.
• Develop and optimize ETL/ELT processes to extract, transform, and load data from a variety of sources into cloud-based data platforms.
• Write efficient, well-tested, production-quality code to support data ingestion, transformation, and delivery.

Cloud & Database Engineering:

• Architect and implement data solutions on cloud platforms (e.g., AWS, Azure, or GCP), leveraging managed services for storage, compute, and orchestration.
• Design, tune, and maintain relational and NoSQL databases to support high-volume, high-availability data workloads.
• Monitor and optimize database and pipeline performance, troubleshooting issues to ensure reliability and scalability.

Data Analysis and Insight Generation:

• Utilize advanced data preparation, modeling, analysis, and visualization techniques to extract insights and knowledge from data.
• Investigate complex business problems and provide actionable, data-driven insights to support strategic decision-making.

Technical Leadership and Collaboration:

• Serve as a technical leader, providing guidance and mentorship to junior engineers in data engineering and analysis best practices.
• Collaborate with cross-functional teams — including Product Management, Business Analysts, and Software Engineering — to design and implement data-driven solutions.

We would love to hear from you if you have:

• Completion of a four-year college degree in a relevant discipline with 4 years of experience in a related field, or completion of an advanced degree (Masters or higher) in an applicable and relevant field, or equivalent experience will be considered in lieu of a degree.
• Strong proficiency in Python for data engineering, automation, and analysis including object-oriented design, modular application development, and production-quality coding practices.
• Experience designing & developing Python based backend services with any of FastAPI/Flask/Django.
• Solid experience on Object oriented practices, APIs, database integrations and dependency management.
• Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP), including their core data and storage services.
• Solid experience with relational and/or NoSQL databases, including schema design, query optimization, and performance tuning.
• Proven experience building and maintaining ETL/ELT pipelines and data workflows.
• Experience in Mortgage Servicing or Financial Services, with an understanding of how technical solutions support business and regulatory needs.
• Strong analytical and problem-solving skills.
• Excellent communication skills and the ability to collaborate effectively across technical and business teams.

Additional Skills/Technical Knowledge Preferred:

• Experience with big-data technologies such as Databricks, Spark, or Dataproc.
• Familiarity with data warehouse platforms (e.g., Snowflake, Redshift, or BigQuery).
• Working knowledge of additional programming languages such as Java, R, Ruby, Scala, or C++.
• Experience with CI/CD, containerization (Docker/Kubernetes), and infrastructure-as-code.
• Knowledge of a mortgage servicer's typical technology ecosystem including servicing systems, default systems, workflow management, data integrations, and data warehouses.
• Experience supporting Agile software development teams.