Senior Python Data Engineer #3606832

Be Part Of A High-Performing Team:
Join a technology team supporting a leading financial services environment where data-driven systems, scalable applications, and reliable engineering practices are critical to business operations. This team works across technical and business groups to build solutions that collect, process, and deliver large volumes of data for analysis, reporting, and downstream application needs. The environment is collaborative, fast-moving, and suited for a senior engineer who can work independently while partnering closely with cross-functional stakeholders.
What's In Store For You:
Engagement: W2 only (no C2C/1099)
This is a hybrid opportunity based in Charlotte, NC, supporting a long-term technical initiative within a financial services technology group. The role offers exposure to back-end engineering, ETL development, APIs, cloud data tooling, and enterprise-scale data workflows.
How You Will Make An Impact

• Build and maintain scalable data pipelines that gather, transform, store, and process large volumes of data.
• Develop server-side applications, APIs, scripts, and back-end components using Python and C#.
• Support ETL development, data quality checks, and optimization of data storage and processing workflows.
• Integrate databases, third-party services, cloud data tools, and internal APIs into reliable application solutions.
• Write clean, efficient, well-documented code and participate in unit testing, debugging, and code reviews.
• Collaborate with business and technical teams to gather requirements, implement solutions, and support CI/CD delivery practices.

Are you an experienced Python data engineering professional ready to make an impact?

• 10+ years of senior-level software engineering, data engineering, or back-end development experience.
• Strong hands-on Python development experience, ideally in data-heavy, API-driven, or enterprise back-end environments.
• Strong SQL skills with experience working across relational databases and large datasets.
• Experience developing ETL pipelines and supporting data quality, transformation, and storage optimization.
• Hands-on experience with cloud data tools such as AWS Glue, Azure Data Factory, or comparable platforms.
• C# development experience for server-side applications, APIs, or enterprise integrations.
• Experience writing unit tests, debugging applications, participating in code reviews, and supporting CI/CD workflows.
• Strong analytical thinking, documentation discipline, and ability to work independently or within Agile teams.
• Financial services or capital markets experience is a plus.

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