Cloud Data Engineer, Business Intelligence

Resurgent Capital Services•Cincinnati, OH

About The Position

Fueled by a fundamental belief in innovation, Resurgent Capital Services is an industry-leading financial services company in our sector. It all began 25 years ago when a small group of successful entrepreneurs had a vision for a new type of asset receivables company. One with a commitment to superior service and a personal touch with every interaction. We believe that demonstrating integrity in everything we do, maintaining a strong commitment to compliance, and doing things the right way is a sustainable business model. We want you to feel like your work has an impact and makes a difference every day. Join us as we develop strategies for change and transform the trajectory of your career! Notice for California Residents - California Privacy Policy Summary As a Cloud Data Engineer, you will be a key architect of our data ecosystem. You’ll own the full software development lifecycle—from initial design and coding to integration testing and deployment. In this role, you aren’t just maintaining systems; you are building innovative data applications that empower our organization. We value autonomy and judgment, looking for a professional with 5+ years of experience who is ready to turn complex data challenges into high-performance production solutions. This position will report to the Vice President of Enterprise Data Engineering.

Requirements

Experience: 5+ years of hands-on experience in data engineering.
SQL Mastery: Strong experience designing data warehouse solutions with expert-level SQL knowledge.
Data Architecture: Deep understanding of databases, data structures, and complex data manipulation.
Pipeline Engineering: Proven ability to create sophisticated data models and end-to-end pipelines for data acquisition, cleansing, and integration.
The Tech Stack: Deep experience with Microsoft SQL Server and proficiency with Databricks.
Coding: Proficiency in C# and/or Python.
Modern Infrastructure: Familiarity with distributed architecture is a significant plus.
Collaborative Mindset: A track record of success in team-oriented, collaborative environments.
Communication: Strong interpersonal skills with a focus on delivering excellent support to internal customers.
Problem Solver: Exceptional analytical skills and a passion for tackling complex technical puzzles.
Full Lifecycle Knowledge: Comprehensive understanding of the SDLC, including source control and lifecycle management tools.

Nice To Haves

Azure Ecosystem: Experience with Azure Analytics, Databases, Storage, and AI/Machine Learning services.
ETL Tools: Experience with SSIS or equivalent enterprise ETL tools.
Statistical Languages: Familiarity with R.

Responsibilities

Architect Impact: Design and develop custom data warehouse solutions that serve as the backbone for executive leadership and data science teams, enabling high-stakes, data-driven decision-making.
Collaborate Across Domains: Partner closely with business analysts, developers, and data scientists to build seamless, user-centric data solutions.
Cloud-Scale ML and AI Delivery: Transform data science prototypes into scalable, reliable production ML and AI solutions.
Optimize Performance: Fine-tune and productionize data integration pipelines to ensure maximum efficiency and reliability.
Build Resilient Systems: Develop proactive "smoke detector" monitoring tools to track and maintain the health of our data ecosystem.
Lead Project Strategy: Take ownership of work estimates, technical roadmaps, and implementation plans.
Stay Ahead of the Curve: Research and integrate emerging technologies, products, and development processes to keep our stack competitive.
Agile Teamwork: Thrive in an agile environment, following best practices and clean coding standards.
Invest in Growth: Actively grow your personal technical skillset while mentoring others to elevate the entire team.

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