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Weekday Financial Data Engineer Jobs in Ohio (NOW HIRING)

This role provides day-to-day technical direction to Data Engineer I and Data Engineer II roles ... Prior work within banking, fintech, mortgage, insurance, or other regulated financial services ...

This role provides day-to-day technical direction to Data Engineer I and Data Engineer II roles ... Prior work within banking, fintech, mortgage, insurance, or other regulated financial services ...

Cloud & Data Engineer

Columbus, OH · On-site

$52 - $69.50/hr

The Cloud & Data Engineer provides technical and consultative support on Huntington's core finance and HR platforms. Duties and Responsibilities: * Partner with Business Analyst to confirm and define ...

This role provides day-to-day technical direction to Data Engineer I and Data Engineer II roles ... Prior work within banking, fintech, mortgage, insurance, or other regulated financial services ...

Senior Data Engineer (Snowflake)

Columbus, OH · On-site +1

$102K - $139K/yr

We are looking for an experienced Senior Data Engineer with strong expertise in Snowflake to help ... Experience working with Finance or Commission-related datasets. Come join us in breaking the mold ...

Showing results 41-60

Weekday Financial Data Engineer information

What is the difference between Weekday Financial Data Engineer vs Financial Data Analyst?

AspectWeekday Financial Data EngineerFinancial Data Analyst
Required CredentialsBachelor's in Computer Science, Finance, or related field; experience with data engineering toolsBachelor's in Finance, Economics, or related field; strong analytical skills
Work EnvironmentData engineering teams, technical departments, often in tech-driven financial firmsFinance departments, investment firms, or banks, focusing on data interpretation
Employer & Industry UsageFinancial institutions, fintech companies, hedge fundsBanking, asset management, investment firms

Weekday Financial Data Engineers focus on building and maintaining data pipelines and infrastructure, while Financial Data Analysts interpret data to support decision-making. Both roles require strong analytical skills, but the engineer role emphasizes technical data management, whereas the analyst role centers on data analysis and reporting.

What are the most commonly searched types of Financial Data Engineer jobs in Ohio?

The most popular types of Financial Data Engineer jobs in Ohio are:

Cloud Data Engineer, Business Intelligence

Cincinnati, OH

$109K - $131K/yr

Full-time

Re-posted 28 days ago


Job description

About Us

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!

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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.

Roles & 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.

Skills & Qualifications

  • 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.

Additional Preferred Skills

  • 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.

Educational Requirements

  • 4-year degree required

Resurgent is an Equal Opportunity employer that is fueled by our diverse and inclusive work environment. Are you excited about this opportunity, but your skills and experience aren't an exact match? We encourage you to apply anyway! You may be just the person we are searching for to fill this or another position. We would love to consider you for the Resurgent team!

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state, or local laws.