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

... for banking and financial services initiatives. This role focuses on analyzing customer, account ... Python for data analysis, feature engineering, statistical analysis, and basic machine learning ...

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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 ...

Azure Data Engineer

Frisco, TX

$107K - $128K/yr

Develop in Python (pandas, PySpark, requests, pytest, logging). Read and modify existing Scala ... Manage Slowly Changing Dimensions (SCD Type 1 & 2) for finance entities. Define partitioning and ...

Senior Cloud Engineer - Full Time

Dallas, TX · On-site

$55.25 - $73.75/hr

Java / Python / Javascript / Golang * Linux & Containerization * Automation & Scripting ... public cloud services for finance industry. This position description identifies the ...

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Python For Finance information

See Dallas, TX salary details

$13

$57

$85

How much do python for finance jobs pay per hour?

As of Jun 7, 2026, the average hourly pay for python for finance in Dallas, TX is $57.99, according to ZipRecruiter salary data. Most workers in this role earn between $47.79 and $65.87 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 Dallas, TX are hiring for Python For Finance jobs? Cities near Dallas, TX with the most Python For Finance job openings:
Financial Crimes Compliance Engineering - Data Analyst, FCC Engineering

Financial Crimes Compliance Engineering - Data Analyst, FCC Engineering

Goldman Sachs

Dallas, TX • On-site

Other

Posted 5 days ago


Goldman Sachs rating

8.3

Company rating: 8.3 out of 10

Based on 25 frontline employees who took The Breakroom Quiz

29th of 141 rated banks


Job description

The Goldman Sachs Compliance Division prevents, detects and mitigates regulatory and reputational risk across the firm, and helps to strengthen the firm's culture of compliance. As an independent control function and part of the firm's second line of defense, Compliance:

  • Assesses the firm's compliance, regulatory and reputational risk
  • Monitors for compliance with new or amended laws, rules and regulations
  • Designs and implements controls, policies, procedures and training
  • Conducts independent testing
  • Investigates, surveils and monitors for compliance risks and breaches
  • Leads the firm's response to regulatory examinations, audits and inquiries

Compliance Engineering empowers these activities by building and operating a suite of software platforms and applications. We are a team of more than 300 engineers and scientists who work on the most complex, mission-critical problems. We have access to the latest technology and to massive amounts of structured and unstructured data. We leverage modern frameworks to build responsive and intuitive UX/UI and Cloud applications, incorporating cutting-edge AI and efficient processes to drive them.

Compliance Engineering user base spans thousands of users globally. We partner with Compliance Officers across divisions, to fully understand the financial products, business strategies, and regulatory regimes. This knowledge enables us to build long-lasting software solutions, and to innovate with a purpose.

Compliance Engineering is looking to fill a Data Analyst role within FCC Engineering.

How will you fulfil your potential

The Financial Crimes Compliance (FCC) Engineering, under Global Compliance, is responsible for Architecture, Design, Development and Implementation of best-in-class software solutions to ensure compliance with regulatory mandates and mitigate any reputational and related risks to the firm. A key component of second line of defense for the firm, FCC Engineering builds and maintains technology solutions for Know Your Customer (KYC), Anti-Money Laundering Detection (AML Monitoring), Sanctions Screening, Anti-Bribery and Corruptions and all other related FCC areas.

With constantly changing regulatory and technology landscape, FCC engineering strives to stay ahead of the curve through continuous innovation.

As a Data Analyst within FCC engineering, you will be a hands-on contributor responsible for developing and supporting scalable FCC data solutions. You will work closely with architects, product partners and compliance stakeholders to implement end-to-end FCC data strategies, curate high quality single source of truth databases and support the development of ML/AI capabilities on AWS/Snowflake and related Cloud ecosystem. This role is implementation heavy and expects strong engineering ownership from design through production support.

In this role, you will contribute to innovation and will be responsible for, among other related functions, the following:

  • Contributes to the design, development, and maintenance of data pipelines and ETL processes for financial crimes compliance applications, ensuring data synchronization with production systems.
  • Assist in the development and maintenance of data products for the "Single Source of Truth" financial crimes compliance data fabric, including on-prem and cloud storage and real-time/batch compute.
  • Support the implementation of storage and compute separation with true data federation to avoid data duplication, eliminate compute resource conflict and ensure cloud-native architecture.
  • Assist in the development and implementation of innovative AI/ML solutions for proactive management of financial crimes compliance risks.
  • Support cloud migration strategies for financial crimes compliance applications.
  • Support the implementation and monitoring of controls for completeness, accuracy and timeliness of data, integrations and applications availability and performance.

Required Qualifications

  • A bachelor's or master's degree in computer science, engineering, data science, or a similar field of study.
  • 5-9 years of hands-on experience with data engineering, ETL development, and data warehousing.
  • Solid experience with Big Data/Cloud Engineering and distributed processing (Batch and streaming concepts).
  • Hands-on experience with AWS (Data platforms, Compute, Storage, Security, Process Orchestration and CI/CD).
  • Proficient hands-on experience with Snowflake including Snowpark, Snow SQL, RBAC, Masking and Snowsight.
  • Experience in implementing controls framework for enterprise-wide complex data and applications landscape.
  • 2-4 years of experience in financial crimes compliance or a related data-intensive field within a global organization.
  • Hands-on experience with enterprise solutions development using Python for data manipulation and scripting.
  • Familiarity with Large Language Models (LLMs) and their potential application in data analysis or compliance.
  • Excellent communication, negotiation and stakeholder engagement skills to create consensus and build collaborative relationships.

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About Goldman Sachs

Sourced by ZipRecruiter

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1869