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Python For Finance Jobs in Plano, TX (NOW HIRING)

Python PySpark Developer

Plano, TX

$48 - $66.25/hr

Duties and responsibilities ● Collaborate with the team to build out features for the data ... Deep understanding of financial industry and their IT systems Preferred qualifications ...

Architect and maintain Python-based services, APIs, and batch or event-driven systems with a focus ... for Mortgage Licensing Act of 2008 (SAFE Act) and/or the Financial Industry Regulatory Authority ...

Programming/scripting skills (JavaScript, Python, REST APIs) a plus. * Five9 certification preferred; experience in CCaaS projects for finance a strong advantage.

Previous experience in Finance * Database background and automation experience. Describe the role ... Implement processes Describe the must have technical skills/experience (ask for alternative/tool ...

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Python For Finance information

See Plano, TX salary details

$12

$56

$82

How much do python for finance jobs pay per hour?

As of Jun 12, 2026, the average hourly pay for python for finance in Plano, TX is $56.11, according to ZipRecruiter salary data. Most workers in this role earn between $46.25 and $63.75 per hour, depending on experience, location, and employer.

What is the difference between Python For Finance vs Quantitative Analyst?

AspectPython For FinanceQuantitative Analyst
Required CredentialsPython skills, finance knowledge, possibly finance-related certificationsAdvanced degrees (e.g., MSc, PhD) in finance, mathematics, or related fields; certifications like CFA
Work EnvironmentFinancial firms, trading desks, investment banks, hedge fundsFinancial institutions, hedge funds, asset management firms, consulting
Employer & Industry UsageUsed for developing trading algorithms, risk modeling, data analysisDevelops quantitative models, risk assessments, trading strategies

Python For Finance focuses on using Python programming to analyze financial data and develop models, often as a technical skill. Quantitative Analysts, however, apply advanced mathematical and statistical techniques to create complex financial models. While both roles require strong analytical skills, Quantitative Analysts typically have higher-level degrees and certifications, and their work involves more theoretical modeling. Python For Finance is often a skill within a Quantitative Analyst's toolkit, but the roles differ in scope and depth.

How does a Python for Finance professional typically collaborate with other departments within a financial organization?

Python for Finance professionals frequently work alongside departments such as data analytics, risk management, and portfolio management. They often translate complex financial models into scalable code, automate data processes, and support decision-making by providing actionable insights through data analysis. Effective communication and collaboration are essential, as these professionals must understand the specific needs of stakeholders and ensure that technical solutions align with business objectives. Regular meetings, code reviews, and cross-functional project teams are common structures within the work environment.

What is Python for Finance?

Python for Finance refers to the use of the Python programming language for financial analysis, modeling, trading, and data visualization. Financial professionals use Python to automate data processing, analyze large financial datasets, build quantitative models, and develop trading algorithms. Its vast ecosystem of libraries such as Pandas, NumPy, and Matplotlib makes Python a popular choice in the finance industry for tasks ranging from risk management to portfolio optimization.

What are the key skills and qualifications needed to thrive as a Python Developer in Finance, and why are they important?

To thrive as a Python Developer in Finance, you need strong programming skills in Python, a solid understanding of financial concepts, and often a degree in computer science, finance, or a related field. Familiarity with financial libraries (such as pandas, NumPy, and QuantLib), databases, and version control systems is typically required, and certifications in data science or finance can be advantageous. Analytical thinking, attention to detail, and effective communication are vital soft skills for interpreting financial data and collaborating with cross-functional teams. These skills are essential to develop robust financial solutions, ensure data accuracy, and drive informed decision-making in a highly regulated and data-driven industry.
What cities near Plano, TX are hiring for Python For Finance jobs? Cities near Plano, TX with the most Python For Finance job openings:
Python PySpark Developer

Python PySpark Developer

Zenith services

Plano, TX

$48 - $66.25/hr

Contractor

Posted 28 days ago


Job description

Duties and responsibilities
● Collaborate with the team to build out features for the data platform and consolidate data
assets
● Build, maintain and optimize data pipelines built using Spark
● Advise, consult, and coach other data professionals on standards and practices
● Work with the team to define company data assets
● Migrate CMS' data platform into Chase's environment
● Partner with business analysts and solutions architects to develop technical
architectures for strategic enterprise projects and initiatives
● Build libraries to standardize how we process data
● Loves to teach and learn, and knows that continuous learning is the cornerstone of every
successful engineer
● Has a solid understanding of AWS tools such as EMR or Glue, their pros and cons and
is able to intelligently convey such knowledge
● Implement automation on applicable processes
Mandatory Skills:
● 5+ years of experience in a data engineering position
● Proficiency is Python (or similar) and SQL
● Strong experience building data pipelines with Spark
● Strong verbal & written communication
● Strong analytical and problem solving skills
● Experience with relational datastores, NoSQL datastores and cloud object stores
● Experience building data processing infrastructure in AWS
● Bonus: Experience with infrastructure as code solutions, preferably Terraform
● Bonus: Cloud certification
● Bonus: Production experience with ACID compliant formats such as Hudi, Iceberg or
Delta Lake
● Bonus: Familiar with data observability solutions, data governance frameworks
Requirements
Bachelor's Degree in Computer Science/Programming or similar is preferred
Right to work
Must have legal right to work in the USA
Job responsibilities
Your experience in public cloud migrations of complex systems, anticipating problems, and finding ways to mitigate risk, will be key in leading numerous public cloud initiatives
Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
Own end-to-end platform issues & help provide solutions to platform build and performance issues on the AWS Cloud & ensure the deliverables are bug free
Drive, support, and deliver on a strategy to build broad use of Amazon's utility computing web services (e.g., AWS EC2, AWS S3, AWS RDS, AWS CloudFront, AWS EFS, AWS DynamoDB, CloudWatch, EKS, ECS, MFTS, ALB, NLB)
Design resilient, secure, and high performing platforms in Public Cloud using JPMC best practices
Measure and optimize system performance, with an eye toward pushing our capabilities forward, getting ahead of customer needs, and innovating to continually improve
Provide primary operational support and engineering for the public cloud platform and debug and optimize systems and automate routine tasks
Collaborate with a cross-functional team to develop real-world solutions and positive user experiences at every interaction
Drive Game days, Resiliency tests and Chaos engineering exercises
Utilize programming languages like Java, Python, SQL, Node, Go, and Scala, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 10+ years applied experience
Hands-on practical experience delivering system design, application development, testing, and operational stability
Advanced in one or more programming language(s) - Java, Python, Go
A strong understanding of business technology drivers and their impact on architecture design, performance and monitoring, best practices
Design and building web environments on AWS, which includes working with services like EC2, ALB, NLB, Aurora Postgres, DynamoDB, EKS, ECS fargate, MFTS, SQS/SNS, S3 and Route53
Advanced in modern technologies such as: Java version 8+, Spring Boot, Restful Microservices, AWS or Cloud Foundry, Kubernetes.
Experience using DevOps tools in a cloud environment, such as Ansible, Artifactory, Docker, GitHub, Jenkins, Kubernetes, Maven, and Sonar Qube
Experience and knowledge of writing Infrastructure-as-Code (IaC) and Environment-as-Code (EaC), using tools like CloudFormation or Terraform
Experience with high volume, SLA critical applications, and building upon messaging and or event-driven architectures
Deep understanding of financial industry and their IT systems
Preferred qualifications, capabilities, and skills
Expert in one or more programming language(s) preferably Java
AWS Associate level certification in Developer, Solutions Architect or DevOps
Experience in building the AWS infrastructure like EKS, EC2, ECS, S3, DynamoDB, RDS, MFTS, Route53, ALB, NLB
Experience with high volume, mission critical applications, and building upon messaging and or event-driven architectures using Apache Kafka
Experience with logging, observability and monitoring tools including Splunk, Datadog, Dynatrace. CloudWatch or Grafana
Experience in automation and continuous delivery methods using Shell scripts, Gradle, Maven, Jenkins, Spinnaker
Experience with microservices architecture, high volume, SLA critical applications and their interdependencies with other applications, microservices and databases
Experience developing process, tooling, and methods to help improve operational maturity