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Data Analyst Fintech Jobs in Texas (NOW HIRING)

Safelease Inc

Data Analyst

Austin, TX · Hybrid

Experience in insurance, fintech, or real estate data environments * Familiarity with property data, underwriting data, or policy/claims datasets * Python for data analysis (pandas, notebooks ...

Brio Real Estate

Associate Data Analyst

Dallas, TX

You have 2+ years of professional experience in fintech or structured products, working with loan ... tape data into a usable state, building complex analytics on asset performance, and creating ...

Acrisure

Data Analyst, Data Intelligence

Austin, TX · On-site

Data Analyst, Data Intelligence Austin, TX (Onsite 4 days per week) Note: This is a full-time role ... A global fintech leader, Acrisure empowers millions of ambitious businesses and individuals with ...

Monitise

Capacity Planner Data Analyst

Stafford, TX

We're Fiserv, a global leader in Fintech and payments, and we move money and information in a way ... Job Title Capacity Planner Data Analyst About your role: You will develop and maintain forecasting ...

New

Sagent

Data Services Analyst Sr

Dallas, TX · On-site

$85K - $107K/yr

Data Services Analyst Senior Worksite: 8840 Cypress Waters Blvd, Suite 190, Coppell, TX 75019 Job ... Sagent is a joint venture that combines Fiserv Inc.'s decades of market-leading fintech expertise ...

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Data Analyst Fintech information

See Texas salary details

$31.7K

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How much do data analyst fintech jobs pay per year?

As of Aug 10, 2026, the average yearly pay for data analyst fintech in Texas is $76,992.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,200.00 and $90,400.00 per year, depending on experience, location, and employer.

Is a data analyst a fintech job?

A data analyst in fintech is a role that involves analyzing financial data to support decision-making, often using tools like Excel, SQL, and data visualization software. This position typically requires understanding financial concepts and may involve working with financial transactions, risk assessment, or customer data within the financial technology industry.

What does a data analyst do in fintech?

A Data Analyst in Fintech collects, processes, and analyzes financial data to uncover trends, optimize business decisions, and improve financial services. They work with big data, statistical models, and visualization tools to provide insights that drive product development, risk management, and customer experience. Their role often involves working with machine learning, SQL, Python, and BI tools to extract meaningful patterns from financial transactions, user behavior, and market trends.

What are the key skills and qualifications needed to thrive as a data analyst in fintech?

To thrive as a Data Analyst Fintech, a strong foundation in data analysis, statistical modeling, and financial acumen—often backed by a relevant degree such as in mathematics, statistics, finance, or computer science—is essential. Proficiency with analytical tools like SQL, Python, R, and specialized fintech platforms as well as certifications like CFA or data analytics certificates is highly valued. Strong problem-solving abilities, attention to detail, and effective communication skills differentiate top performers, enabling them to present complex findings clearly. These skills are crucial for extracting actionable insights from financial data and supporting data-driven decision-making in the rapidly evolving fintech industry.

What types of teams or departments do data analysts typically collaborate with in a fintech company?

Data Analysts in fintech companies frequently work alongside product development, engineering, risk management, and business strategy teams to analyze data and provide actionable insights. Their work often contributes to fraud detection, customer experience optimization, and financial forecasting, requiring close communication with both technical and non-technical stakeholders. Collaboration is key, as insights generated by data analysts often guide the direction of products and services and influence important business decisions. This cross-functional interaction not only broadens professional experience but also provides opportunities for career growth within different areas of the fintech sector.

What are the most commonly searched types of Data Analyst Fintech jobs in Texas? The most popular types of Data Analyst Fintech jobs in Texas are:
What are popular job titles related to Data Analyst Fintech jobs in Texas? For Data Analyst Fintech jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Data Analyst Fintech jobs in Texas look for? The top searched job categories for Data Analyst Fintech jobs in Texas are:
Data Analyst Fintech jobs near you
Infographic showing various Data Analyst Fintech job openings in Texas as of July 2026, with employment types broken down into 100% Full Time. Highlights an 65% In-person, 9% Hybrid, and 26% Remote job distribution, with an average salary of $76,992 per year, or $37 per hour.

Data Analyst

SafeLease Insurance Services LLC

Austin, TX • On-site

Full-time

Medical, PTO

Re-posted 18 days ago

Job description

About SafeLease
At SafeLease, we're rethinking how P&C insurance is sold in an age of technological change. We believe the industry's biggest inefficiencies aren't technical problems - they're structural ones. And we're building the team to tackle them.
SafeLease is a profitable insurance business that designs, underwrites, and distributes specialty coverage for commercial property owners and their tenants. Most insurance companies either distribute products or bear the risk - we do both. We back our policies with our own capital, which means we control the full stack: product design, tech, and the speed at which we move. That end-to-end ownership lets us offer customers real flexibility, saving time and money for more than 4,000 properties insured for billions in value nationwide.
We're a team of 70, growing over 100% annually, and we've done it without sacrificing profitability or culture. Here, you'll get high discretion and a wide aperture of problems to solve. We embrace the newest technologies, move fast together, and operate with the intensity of a small company where every person's work is visible. If you're looking for a place to sharpen your craft alongside people who take their work seriously, you'll fit right in.
This position requires working in the office 3 days per week in either New York City or Austin, TX. Applicants who are unable to work from either office location or are not willing to relocate will not be considered.
About The Role
We're looking for an Analytics Engineer / Data Analyst to unlock the value of our data assets by transforming and presenting data in a way that drives action. You'll be a key voice in turning data signals into business decisions.
This isn't a "pull reports on request" role. You'll build the infrastructure that makes reliable reporting possible, go deep on unexplained patterns, and proactively surface insights that change how the business operates. You'll work closely with pricing, sales ops, product, and leadership - translating between technical data realities and business questions that don't always arrive in clean form.
What You'll Do
Data Modeling & Transformation
  • Design, build, and maintain dbt models that transform raw source data into clean, well-documented, analytics-ready tables in Snowflake
  • Establish and enforce naming conventions, testing standards, and documentation practices across the dbt project
  • Own the semantic layer - ensuring consistent metric definitions that all stakeholders can trust

Reporting & Dashboards
  • Build and maintain executive and department-level dashboards that communicate performance clearly and without ambiguity
  • Partner with stakeholders across pricing/actuarial, sales, business development, and operations to understand reporting needs and translate them into durable, self-serve solutions
  • Distinguish between dashboards that inform decisions and dashboards that create noise - and build accordingly

Analysis & Insight
  • Conduct deep-dive analyses to explain anomalies, validate hypotheses, and uncover signals in messy data
  • Synthesize findings into clear, concise narratives - written, visual, and verbal - appropriate for technical and non-technical audiences
  • Proactively identify inflection points in the data and connect them to operational or market causes
  • Contribute to strategic decisions by framing tradeoffs with data, not just describing what happened

Data Quality & Governance
  • Instrument data quality checks and alerting so issues surface before they reach decision-makers
  • Maintain data dictionaries and lineage documentation that make the platform legible to the broader organization
  • Partner with engineering to ensure upstream source data lands in a state that's trustworthy and usable

Required
  • 3-5+ years of experience in analytics engineering, data analysis, or a hybrid role
  • Strong SQL - you write queries from scratch, optimize them, and know when a query is telling you something wrong
  • Hands-on experience with dbt (Core or Cloud) - model structure, ref/source, tests, documentation, incremental strategies
  • Proficiency with Snowflake or a comparable cloud data warehouse
  • Experience building dashboards in Metabase, Looker, Mode, Tableau, or similar
  • Proven ability to go from a vague business question to a structured analysis to a clear recommendation
  • Strong written communication - your documentation and stakeholder write-ups are as clear as your SQL

Strong Plus
  • Experience in insurance, fintech, or real estate data environments
  • Familiarity with property data, underwriting data, or policy/claims datasets
  • Python for data analysis (pandas, notebooks, scripting)
  • Exposure to data modeling patterns - star schema, slowly changing dimensions, wide tables - and when to use which
  • Experience working in a startup or early-stage data team where you had to build the foundation, not just extend it
What Success Looks Like
In your first 90 days, you've learned the data landscape, identified the highest-leverage gaps in our current modeling and reporting, and shipped your first set of dbt models and dashboards into production. Stakeholders know who to come to with data questions - and the answers they get are accurate and on time.
At six months, you've meaningfully improved data reliability and self-serve access across at least two business functions. You've led at least one significant deep-dive that influenced a real business decision.
At a year, you are the person who knows more about how SafeLease data works - end to end - than almost anyone else in the company. You're raising the bar for how we define, measure, and act on data, and you're doing it in a way that makes the whole team better.
Why SafeLease?
The tech: Our prospects convert fast because we're solving real problems and delivering serious value to commercial real estate owners.
The team: We're a team of seasoned pros and sharp operators who know how to move fast and build smart. High standards, low ego.
The stability: We're well-funded, growing fast, and we make sure our team shares in that success with competitive pay and equity.
The employee experience: We also offer unlimited PTO, full health benefits, flexible work setups, and the kind of culture where people want to show up to do their best work.
If you don't have all the qualifications listed, don't worry! We understand everyone's career path is unique and still encourage you to apply if you feel this role is aligned with your career trajectory.
Employment at SafeLease is contingent upon a satisfactory verification of a general and criminal background check.

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