Senior Data Platform Engineer

Casepoint

• $120K — $145K *
Finance & Insurance
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 6+ years of software engineering or advanced data engineering experience focusing on financial data platforms.
  • Proficiency in languages like C, C++, Java, JavaScript, PHP, and Python, with expert-level SQL skills.
  • Experience building automated data acquisition tools and frameworks with enterprise databases.
  • Ability to design high-performance data structures for enterprise data presentation tools.
  • Proven leadership in managing complex technical initiatives and mentoring engineers.

Responsibilities

  • Design and maintain robust data pipelines and automated data processes.
  • Engineer optimized data structures tailored for financial reporting.
  • Architect scalable multi-region data warehouse integrations, focusing on data transformation.
  • Drive complex software projects from inception to completion, addressing risks and dependencies.
  • Refine data infrastructure using modern methodologies and CI/CD practices.
  • Collaborate with finance and BI teams to improve data visualization capabilities.
  • Mentor junior engineers and promote best practices in software engineering.

Benefits

  • Remote work eligibility with a preference for candidates located in the DMV area.
  • Opportunity for in-person collaboration when needed.
  • Consideration given to candidates from various states based on business needs.
  • Exposure to complex technical initiatives and cutting-edge data engineering practices.
Full Job Description
We are looking for a Senior Data Platform Engineer to lead high-complexity data development initiatives, architect resilient multi-region data systems, and drive multi-team technical projects. You will serve as a financial data management and reporting expert, focusing on data engineering to build automated data acquisition tools, develop scalable update processes, and engineer optimized data structures that power financial reporting and enterprise data presentation tools.

Work Location

This position is eligible for remote work. Priority consideration will be given to candidates based in the DMV (DC, MD, VA) area to support occasional in-person collaboration.

We also welcome applications from candidates located in the following states, based on business needs and the availability of specialized talent:

AR, AZ, CA, CO, CT, DE, FL, GA, IL, IN, KS, KY, LA, MA, MI, MN, NC, NH, NJ, NM, NV, NY, OH, OK, OR, PA, SC, TX, WA, WI, WV, WY.

At this time, we are only able to consider candidates residing in these states.

Key Responsibilities
  • Design, build, and maintain robust data pipelines, software codebases, and automated data acquisition and update processes using modern data engineering frameworks.
  • Engineer optimized data structures, schemas, and semantic layers tailored to support financial reporting and executive dashboards within enterprise data presentation tools.
  • Architect scalable, resilient multi-region database and data warehouse integration layers (including Oracle backends) focusing on programmatic data extraction and transformation.
  • Drive complex, multi-team data infrastructure software projects from conception to completion while anticipating systemic risks and cross-functional dependencies.
  • Refine and automate data infrastructure using modern provisioning, software design patterns, and CI/CD pipelines.
  • Partner with finance, product, and BI teams to build reliable extraction layers and elevate enterprise visualization capabilities.
  • Mentor junior engineers and champion software engineering best practices across the engineering lifecycle.

Required Qualifications
  • 6+ years of software engineering or advanced data engineering experience focused on building and supporting financial data platforms and pipelines.
  • Strong software development background with proficiency in programming languages such as C, C++, Java, JavaScript, PHP, and python along with expert-level skills in SQL, PL/SQL, and query optimization.
  • Proven experience building fully automated data acquisition tools, extraction frameworks, and complex data update workflows interacting with enterprise databases (such as Oracle).
  • Demonstrated expertise in designing high-performance data structures and semantic layers optimized for modern enterprise data presentation tools.
  • Proven ability to lead complex technical initiatives independently and mentor engineering talent.

Preferred Qualifications
  • Deep familiarity with financial reporting structures and automated financial data pipelines.
  • Experience architecting zero-downtime, distributed data systems across cloud providers.


  • Strong background in CI/CD, software testing frameworks, and proactive risk mitigation.
  • Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical discipline.


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