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Python Data Analyst Jobs in Albuquerque, NM (NOW HIRING)

... as Python, R, Visual Basic, or similar. โ€ข Strong statistical, mathematical, and analytical ... and refine data models. โ€ข Demonstrated capability to analyze operations, evaluate model ...

Data Analytics

Albuquerque, NM ยท On-site

$71K - $150K/yr

Job Title: Data Analytics Job Category: Information Technology Time Type: Full time Minimum ... Proficiency in at least one programming language such as Python, R, Visual Basic, or similar.

Digital Analyst Internships

Albuquerque, NM ยท On-site

$95K - $112K/yr

About Digital Analyst Roles at Danaher Are you passionate about data, customer experience, and ... Basic programming or scripting experience in Python, SQL, or JavaScript * Experience with Sitecore ...

Comfortable with Python. * Experience working within data platforms like Databricks/Snowflake, and analytics modeling platforms such as Tableau * Strong analytical and problem-solving skills with the ...

Data Engineer

Albuquerque, NM ยท On-site

$111K - $133K/yr

Here, you'll work with a multi-disciplinary team of data analysts, engineers, scientists ... using Python for data processing and automation * 1+ years of experience with cloud services

Data Engineer

Albuquerque, NM

$111K - $133K/yr

Here, you'll work with a multi-disciplinary team of data analysts, engineers, scientists ... using Python for data processing and automation * 1+ years of experience with cloud services

Data Engineer

Albuquerque, NM ยท On-site

$111K - $133K/yr

Here, you'll work with a multi-disciplinary team of data analysts, engineers, scientists ... using Python for data processing and automation * 1+ years of experience with cloud services

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Python Data Analyst information

See Albuquerque, NM salary details

$33K

$80.1K

$131.8K

How much do python data analyst jobs pay per year?

As of Jun 25, 2026, the average yearly pay for python data analyst in Albuquerque, NM is $80,105.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,600.00 and $94,000.00 per year, depending on experience, location, and employer.

What does a Python Data Analyst do?

A Python Data Analyst leverages the Python programming language to collect, process, and analyze large sets of data. They use tools and libraries like Pandas, NumPy, and Matplotlib to clean data, perform statistical analysis, and create visualizations that help organizations make data-driven decisions. Their role often involves extracting insights from complex datasets, automating data workflows, and communicating findings to stakeholders through reports or dashboards. Python Data Analysts play a crucial part in turning raw data into actionable business intelligence.

How do Python Data Analysts typically collaborate with other departments within an organization?

Python Data Analysts often work closely with teams such as marketing, finance, and product development to provide data-driven insights that inform business decisions. They regularly participate in cross-functional meetings to understand departmental objectives, gather requirements for data analysis, and present their findings in an accessible manner. Effective communication and the ability to translate technical results into actionable recommendations are essential, as analysts often act as a bridge between technical data and non-technical stakeholders.

What is the difference between Python Data Analyst vs Data Scientist?

AspectPython Data AnalystData Scientist
Required SkillsPython, SQL, data visualization, statistical analysisPython, R, machine learning, statistical modeling
Work EnvironmentBusiness analytics, reporting, data cleaningAdvanced modeling, predictive analytics, research
Industry UsageFinance, marketing, healthcare, retailTech, finance, research, AI development

While both roles require Python and data analysis skills, Data Scientists typically engage in more complex modeling and machine learning, whereas Python Data Analysts focus on data cleaning, visualization, and reporting to support business decisions.

What Does a Python Data Analyst Do?

As a Python data analyst, you use the Python programming language to develop tools for data mining, analysis, and data visualization. You typically develop a script to meet the specific data needs of your client or employer. Then, you test your code and perform debugging duties before deploying it in a live environment. Some data analysts also have algorithm creation responsibilities. In this case, after creating and testing an algorithm, you use Python with your algorithm to interpret data. You also develop reports to show to your clients or employers, and you may code a web app or interface that clients can use to visualize data sets.

Are Python coders still in demand?

Python data analysts are currently in high demand due to the language's versatility in data analysis, machine learning, and automation. Skills in libraries like Pandas, NumPy, and experience with data visualization tools increase employability across various industries.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst. Many professionals successfully transition into data analysis at various ages by acquiring skills in programming languages like Python or SQL, and gaining experience with data visualization tools. Employers value skills and experience over age, and continuous learning can help you stay competitive in the field.

What are the key skills and qualifications needed to thrive as a Python Data Analyst, and why are they important?

To thrive as a Python Data Analyst, you need strong analytical skills, a solid grasp of statistics, and proficiency in Python programming, often supported by a degree in data science, mathematics, or a related field. Familiarity with data analysis libraries like pandas and NumPy, visualization tools such as Matplotlib or Seaborn, and experience with data querying languages like SQL are typically required. Attention to detail, critical thinking, and effective communication help you derive insights and present findings clearly to stakeholders. These skills and qualities are vital for transforming raw data into actionable business intelligence and supporting data-driven decision-making.

Is Python useful for data analysts?

Python is highly useful for data analysts as it offers powerful libraries like Pandas, NumPy, and Matplotlib for data manipulation, analysis, and visualization. It is widely used in the industry for automating tasks, building data pipelines, and performing statistical analysis, making it a valuable skill for the role.

Will AI replace data analysts?

AI is transforming the role of data analysts by automating routine tasks such as data cleaning and basic analysis, but it is unlikely to fully replace them. Data analysts are needed to interpret complex insights, make strategic decisions, and develop models that require domain expertise and critical thinking. Skills in programming, data visualization, and understanding AI tools remain valuable in this evolving field.
What are the most commonly searched types of Python Data Analyst jobs in Albuquerque, NM? The most popular types of Python Data Analyst jobs in Albuquerque, NM are:
What job categories do people searching Python Data Analyst jobs in Albuquerque, NM look for? The top searched job categories for Python Data Analyst jobs in Albuquerque, NM are:
Infographic showing various Python Data Analyst job openings in Albuquerque, NM as of June 2026, with employment types broken down into 1% Internship, 71% Full Time, 7% Part Time, 18% Contract, and 3% Nights. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $80,105 per year, or $38.5 per hour.
IT Data Platform Data Engineer (2 Openings)

IT Data Platform Data Engineer (2 Openings)

PNM Resources

Albuquerque, NM โ€ข On-site

$128K - $161K/yr

Full-time

Posted 25 days ago


Job description

POSTING DEADLINE
This position is posted until filled.
JOB DESCRIPTION
IT Data Platform Data Engineer
Salary Grade: G05
Minimum Midpoint Maximum
$94,831 - $128,022 - $161,213
The following statements are intended to describe the general nature and level of work being performed. They are not intended to be construed as an exhaustive list of all responsibilities, duties, and skills.
SUMMARY
Under limited direction, leads the design, build, and maintenance of enterprise-scale data pipelines and data platforms that enable advanced analytics, reporting, and AI initiatives. Partners with business and IT leadership to shape strategic data requirements, ensure robust data integration, and deliver timely access to high-quality data across the organization. Champions data engineering best practices, drives governance and security compliance, and leads continuous improvement of enterprise data infrastructure.
ESSENTIAL DUTIES AND RESPONSIBILITIES.
Leads the design, development, and maintenance of automated data pipelines for ingesting, transforming, and storing complex structured and unstructured data from multiple evolving sources
Drives collaboration with BTS and business leadership to architect reliable, scalable enterprise data solutions supporting analytics, reporting, and AI use cases
Architects, builds, and oversees data integration processes, ETL/ELT workflows, and orchestration frameworks to ensure availability, performance, and resilience
Establishes and enforces data quality, completeness, accuracy, and timeliness through advanced validation, proactive monitoring, and remediation processes
Defines and implements sophisticated data models and structures optimized for enterprise analytics and advanced analysis
Guides strategy for cloud and on-premises data platforms, including data lakes, data warehouses, and next-generation analytics environments
Leads and mentors data analysts, data scientists, and junior engineers in feature engineering and model readiness
Develops and governs metadata management, lineage, and documentation standards while driving adoption across the enterprise
Owns compliance with data security, privacy, and regulatory requirements in alignment with enterprise policies
Leads performance tuning, capacity planning, and optimization efforts for data pipelines and data storage
Oversees platform health and proactively resolves complex, systemic data pipeline issues
Authors and maintains advanced data engineering designs, standards, and operational procedures
Exercises expert judgment in evaluating technical options, balancing cost, performance, scalability, security, and maintainability
Identifies and drives innovation opportunities to modernize and expand enterprise data platforms
COMPETENCIES
Expert understanding of enterprise data architecture, integration patterns, and large scale data platforms
Demonstrates mastery of SQL and expert proficiency in Python, data modeling, and data integration tools
Diagnoses and resolves complex data flows, system dependencies, and platform level issues
Evaluates technical solutions strategically, considering long term scalability, cost, performance, and risk
Champions innovation, challenges assumptions, and leads adoption of emerging technologies
Leads and influences across matrixed organizations, driving consensus and alignment
Facilitates enterprise coordination across data, analytics, engineering, and IT functions
Defines, institutionalizes, and enforces engineering standards, best practices, and architectural guidelines
Communicates persuasively with technical teams and executive audiences
Interprets complex technical and business documentation and converts it into actionable engineering plans
Rapidly acquires, unlearns, and instills advanced tools, frameworks, and engineering methodologies
Builds trust with internal partners and cross functional teams through credibility and technical authority
QUALIFICATIONS
Bachelors degree in Computer Science, Information Systems, Engineering, or related field, with seven to nine years of progressively responsible experience in data engineering, data integration, or analytics platforms, or an equivalent combination of advanced education and experience.
A masters degree or specialized certifications preferred
CERTIFICATES, LICENSES AND REGISTRATIONS (Preferred)
Microsoft Certified: Power BI Data Analyst Associate
Tableau Desktop Certified Associate
IBM Data Analyst Professional Certificate
SAS Certified Advanced Analytics Professional (Using SAS 9)
Data Science Council of America (DASCA)
Databricks Certified Data Analyst Associate
Google, AWS, Microsoft Azure Data Analytics certifications
WORK ENVIRONMENT AND PHYSICAL REQUIREMENTS
Office environment.
Travel approximately 10% of the time.
Ability to sit, stand, walk, and stoop as required.
Manual dexterity and good vision required.
Must occasionally lift and/or move up to 10 pounds.
SAFETY AND ADA STATEMENT
Safety Statement:
Safety is a core value at (TXNM Energy/PNM/TNMP) and our vision, "everyone goes home safe", reflects our commitment to promoting an environment conducive to learning, improving and building safety practices. Our safety value is built upon the belief that every employee deserves to work in an environment free from harm.
Americans with Disabilities Act (ADA) Statement:
If you require assistance with the job application process due to a disability, please contact HR ADA Analyst, at 505-241-4627.
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