Senior Data Services Engineer — Remote Data Pipelines

United States Digital Space LLC

United States

Hybrid

USD 120,000 - 190,000

Full time

14 days+

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Benefits offered by this job

Remote/Hybrid workplace options

Health Benefits

Tuition Reimbursement

Paid Family Leave

401(k) Matching

Pet Insurance

In-person and Virtual Social Events

Career Pathing

Focus Time Fridays

Job summary

United States Digital Space LLC is a leading Mortgage Servicing, SaaS-based company seeking a Senior Data Services Engineer to design, build, and optimize data solutions powering our Mortgage Servicing platform. You will apply Python, cloud, and database expertise to enable data-driven decisions across the organization.

You will lead data pipelines, ETL/ELT processes, and collaborate with product, analytics, and software teams.

Qualifications

Completion of a four-year college degree in a relevant discipline with 4 years of experience in a related field, or an advanced degree in applicable field, or equivalent experience.
Strong proficiency in Python for data engineering, automation, and analysis including OO design and production-quality coding practices.
Experience designing & developing Python-based backend services with FastAPI/Flask/Django.
Solid experience with APIs, database integrations and dependency management.
Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP) and core data services.
Solid experience with relational and/or NoSQL databases; schema design and performance tuning.
Proven experience building and maintaining ETL/ELT pipelines and data workflows.
Experience in Mortgage Servicing or Financial Services with regulatory understanding.
Strong analytical and problem-solving skills; excellent cross-functional communication.

Responsibilities

Design, build, and maintain scalable data pipelines and services using Python and modern data engineering frameworks.
Develop and optimize ETL/ELT processes to load data into cloud-based data platforms.
Write production-quality, well-tested code for data ingestion, transformation, and delivery.
Architect and implement data solutions on cloud platforms (AWS/Azure/GCP) with managed services.
Design, tune, and maintain relational and NoSQL databases for high-volume workloads.
Monitor and optimize data pipelines for reliability and scalability; troubleshoot issues.
Mentor junior engineers and provide guidance on data engineering best practices.
Collaborate with Product, Analytics, and Software teams to implement data-driven solutions.