IT Data Platform Data Engineer (2 Openings)

Public Service Company of New Mexico (PNM); Albuquerque (NM); On-site; USD 94,831 - 161,213; Full time

Job summary

Public Service Company of New Mexico (PNM) seeks an IT Data Platform Data Engineer to design, build, and maintain enterprise-scale data pipelines. The role partners with IT leadership to enable advanced analytics and AI initiatives with robust data integration and timely access to high-quality data.

Responsibilities include data modeling, cloud/on-prem architectures, and governance. You will mentor engineers, drive standards, and ensure security and regulatory compliance across the data platform.

Qualifications

• Bachelor's degree in CS/IS/Engineering with 7–9 years of data engineering, data integration, or analytics platform experience.
• Masters degree or specialized certifications are preferred.
• Proficiency in SQL, Python, data modeling, and data integration tools is required.

Responsibilities

• Lead design, build, and maintenance of automated data pipelines for diverse data sources.
• Architect and oversee ETL/ELT workflows and orchestration for reliability and performance.
• Ensure data quality, governance, and security across enterprise data platforms.
• Mentor junior engineers and analysts; drive data engineering standards and best practices.

Skills

SQL

Python

Data modeling

Data integration

Education

Bachelor's degree in Computer Science / Information Systems / Engineering

Masters degree or specialized certifications preferred

Tools

ETL/ELT frameworks

Job description

$94,831 - $128,022 - $161,213

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.