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Full Time Python Data Analysis Jobs in Albuquerque, NM

Booz Allen Hamilton

Data Architect, Senior

Albuquerque, NM

$65.25 - $87.25/hr

As organizations increasingly depend on cloud platforms, analytics, and AI/ML to drive mission ... Our architecture, pipelines, and tooling are built on modern Python frameworks. You'll be designing ...

Booz Allen Hamilton

Data Engineer

Albuquerque, NM · On-site

$111K - $133K/yr

Here, you'll work with a multi-disciplinary team of data analysts, engineers, scientists ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton, Inc.

Data Engineer

Albuquerque, NM · On-site

$111K - $133K/yr

Here, you'll work with a multi-disciplinary team of data analysts, engineers, scientists ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

CACI International, Inc.

NAVWAR Engineer

Albuquerque, NM · On-site

Engineering Time Type: Full time Minimum Clearance Required to Start: Secret Employee Type: Regular ... Experience coding for data analytics and visualization, utilizing languages such as Python, R, or ...

Booz Allen Hamilton, Inc.

Data Architect

Albuquerque, NM · On-site

$61.75 - $79.50/hr

As a Junior Data Architect, you'll work alongside engineers, analysts, and business stakeholders to ... Experience using Python for data processing, automation, or scripting * Knowledge of ETL and ELT ...

Booz Allen Hamilton

Data Architect

Albuquerque, NM · On-site

$61.75 - $79.50/hr

Responsibilities : • Design and maintain logical and physical data models that support analytics ... Python for data processing, automation, or scripting • Knowledge of ETL and ELT processes and ...

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Full Time Python Data Analysis information

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How much do full time python data analysis jobs pay per hour?

As of Jul 27, 2026, the average hourly pay for full time python data analysis in Albuquerque, NM is $56.82, according to ZipRecruiter salary data. Most workers in this role earn between $46.83 and $64.57 per hour, depending on experience, location, and employer.

Can I be a data analyst with just Python?

A data analyst role typically requires knowledge of multiple tools and skills, including SQL, Excel, and data visualization software, in addition to Python. While Python is a valuable skill for data analysis, relying solely on it may limit your ability to perform all necessary tasks effectively. Developing a broader skill set can improve job prospects and performance in data analysis roles.

What are some common challenges faced by Full Time Python Data Analysts and how can they be addressed?

Full Time Python Data Analysts often encounter challenges such as handling large, messy datasets and ensuring data accuracy. Navigating complex data sources or integrating data from multiple platforms can also be demanding. To address these challenges, analysts typically leverage robust Python libraries like pandas and NumPy for efficient data wrangling, and collaborate closely with data engineering teams to clarify requirements and resolve data discrepancies. Regular code reviews and adopting best practices in data validation help maintain data integrity and streamline analysis workflows.

Is 40 too late for data science?

Full Time Python Data Analysis roles often value skills and experience over age, and many professionals transition into data science later in their careers. Learning relevant tools like Python, SQL, and machine learning can help you enter the field regardless of age, and continuous education or certifications can improve your prospects.

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

To thrive as a Full Time Python Data Analyst, you need strong analytical skills, proficiency in Python programming, and a solid understanding of statistics, typically supported by a relevant degree in computer science, mathematics, or a related field. Familiarity with data analysis libraries (such as pandas and NumPy), data visualization tools (like Matplotlib or Seaborn), and experience with SQL databases are commonly required. Attention to detail, problem-solving abilities, and effective communication skills distinguish top performers in this role. These skills and qualities are crucial for extracting actionable insights from data and effectively collaborating with stakeholders to inform business decisions.

What is the difference between Full Time Python Data Analysis vs Data Scientist?

AspectFull Time Python Data AnalysisData Scientist
Required CredentialsBachelor's in Data Analysis, Statistics, or related field; Python skillsBachelor's or higher in Data Science, Computer Science, or related; Python, R, ML certifications
Work EnvironmentCorporate, finance, marketing, or tech companies; data-focused teamsResearch labs, tech firms, finance, or healthcare; data modeling and research
Employer & Industry UsageCommon in industries needing data reporting and insightsUsed for predictive modeling, machine learning, and advanced analytics

Full Time Python Data Analysts focus on interpreting data and generating reports using Python, while Data Scientists develop models and algorithms for predictive analytics. Both roles require Python skills, but Data Scientists typically have more advanced statistical and machine learning expertise. The roles often overlap, but Data Scientists tend to work on more complex modeling tasks, whereas Data Analysts focus on data interpretation and visualization.

What is a Full Time Python Data Analysis job?

A Full Time Python Data Analysis job involves using the Python programming language to collect, clean, analyze, and visualize data in order to help organizations make data-driven decisions. Professionals in this role work with large data sets, utilize libraries like pandas and NumPy, and often create reports or dashboards to communicate their findings. They may collaborate with other teams to identify trends, solve business problems, and provide actionable insights based on the data.

Will AI replace a data analyst?

AI tools can automate routine data processing and basic analysis tasks, but data analysts are essential for interpreting complex data, making strategic decisions, and providing context. The role of a data analyst involves skills like critical thinking, domain knowledge, and communication that are not easily replaced by AI. Therefore, while AI may augment the work of data analysts, it is unlikely to fully replace them in the near future.
What are the most commonly searched types of Python Data Analysis jobs in Albuquerque, NM? The most popular types of Python Data Analysis jobs in Albuquerque, NM are:
Full Time Python Data Analysis jobs near you
Infographic showing various Full Time Python Data Analysis job openings in Albuquerque, NM as of July 2026, with employment types broken down into 100% Full Time. Highlights an 91% In-person, 2% Hybrid, and 7% Remote job distribution, with an average salary of $118,192 per year, or $56.8 per hour.
IT Data Platform Data Engineer (2 Openings)

IT Data Platform Data Engineer (2 Openings)

PNM Resources

Albuquerque, NM • On-site

$128K - $161K/yr

Full-time

Posted 28 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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