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Freelance Databricks Data Engineer Jobs in Albuquerque, NM

Data Integration: Collaborate with cross-functional teams such as IT and engineering to integrate ... Experience working within data platforms like Databricks/Snowflake, and analytics modeling ...

Freelance Databricks Data Engineer information

See Albuquerque, NM salary details

$14

$46

$128

How much do freelance databricks data engineer jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for freelance databricks data engineer in Albuquerque, NM is $46.24, according to ZipRecruiter salary data. Most workers in this role earn between $23.56 and $59.90 per hour, depending on experience, location, and employer.

What is a freelance Databricks data engineer?

Freelance Databricks Data Engineers are independent professionals who specialize in designing, building, and maintaining data pipelines and analytics solutions using the Databricks platform. They work on a contract basis, often helping organizations with data integration, ETL processes, and leveraging Apache Spark for big data analytics. These engineers typically have expertise in cloud platforms, SQL, Python, and other data engineering tools, and they offer flexible support based on project needs.

What are the key skills and qualifications needed to thrive as a freelance Databricks data engineer?

To thrive as a Freelance Databricks Data Engineer, you need strong skills in data engineering, SQL, Python or Scala, and a solid understanding of big data concepts, often supported by a degree in computer science or related fields. Proficiency with Databricks, Apache Spark, cloud platforms (such as AWS or Azure), and relevant certifications (like Databricks Certified Data Engineer) is highly valued. Excellent problem-solving, communication, and self-management skills are essential for collaborating remotely with clients and handling diverse projects. These skills enable efficient data pipeline development, scalable analytics, and successful client delivery in dynamic freelance environments.

How do freelance Databricks data engineers typically collaborate with client teams during projects?

Freelance Databricks Data Engineers often work remotely and interact with client teams through regular virtual meetings, project management platforms, and collaboration tools like Slack or Microsoft Teams. Clear communication is crucial, as you'll coordinate closely with data scientists, analysts, and IT stakeholders to understand requirements, deliver solutions, and troubleshoot issues. Establishing a structured workflow and providing frequent progress updates help ensure alignment and project success. Flexibility and proactive problem-solving are especially important in adapting to each client's unique data infrastructure and business goals.

What is the difference between Freelance Databricks Data Engineer vs Freelance Data Engineer?

AspectFreelance Databricks Data Engineer

Required SkillsProficiency in Databricks, Spark, Python, SQL, cloud platforms
Work EnvironmentRemote, project-based, client-specific
CertificationsDatabricks certifications, cloud platform credentials
Industry UsageData analytics, big data projects, AI/ML integrations

Freelance Databricks Data Engineers specialize in building and maintaining data pipelines using Databricks and Spark, often working on big data projects in cloud environments. Freelance Data Engineers may have broader skills across various tools and platforms but might not focus specifically on Databricks. Both roles are remote, project-based, and require similar certifications, but the Databricks-specific expertise makes the Freelance Databricks Data Engineer more specialized in Databricks ecosystems.

What are popular job titles related to Freelance Databricks Data Engineer jobs in Albuquerque, NM?

For Freelance Databricks Data Engineer jobs in Albuquerque, NM, the most frequently searched job titles are:

Infographic showing various Freelance Databricks Data Engineer job openings in Albuquerque, NM as of August 2026, with employment types broken down into 60% Full Time, and 40% Contract. Highlights an 52% In-person, and 48% Remote job distribution, with an average salary of $96,186 per year, or $46.2 per hour.

IT Data Platform Data Engineer

PNM Resources

Albuquerque, NM • On-site

$128K - $161K/yr

Full-time

Posted 6 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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