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Data Engineer Jobs in Alaska (NOW HIRING)

Pacs

$100/hr

Stay current with best practices in data engineering, analytics, and the Microsoft Fabric ecosystem. * Write Python scripts and Jupyter notebooks for data extraction, transformation, and automation ...

Glacier Services Inc.

Automation Technician

Prudhoe Bay, AK · On-site

$47K/yr

Data Engineering / Analytics * Creates data pipelines and data integrations in databases, data warehouses and data lakes working with various cloud and on-premises technologies * Skilled at data ...

Sedgwick

AI Data Scientist Sr.

Minto, AK

$120K - $160K/yr

Strong data exploration, data wrangling and feature engineering skills * Knowledge of application of supervised/unsupervised ML techniques * Thorough knowledge of SQL to query relational databases

York Risk Services

AI Data Scientist Sr.

Minto, AK

$120K - $160K/yr

Strong data exploration, data wrangling and feature engineering skills * Knowledge of application of supervised/unsupervised ML techniques * Thorough knowledge of SQL to query relational databases

Cisco

Software Engineer, Backend

Juneau, AK · On-site

$152K - $219K/yr

Meet the Team The Time Series Data (TSD) team builds andoperatesthe time-series database ... Programming experience in Rust, Scala, Python. * Experience with observability tooling such ...

Accura Engineering

Project Engineer-Electrical

Juneau, AK · On-site

... data centers, and other complex electrical-engineering related elements found in large and complex ... buildings and utility plants. * Previous experience with US Army Corp of Engineers projects will ...

WSP

Early Career Geotechnical Engineer

Anchorage, AK · On-site

Under general supervision, assist with collecting, compiling, and analyzing data from the physical ... Perform routine geotechnical engineering functions and provide entry-level technical assistance on ...

WSP

Early Career Geotechnical Engineer

Anchorage, AK

Under general supervision, assist with collecting, compiling, and analyzing data from the physical ... Perform routine geotechnical engineering functions and provide entry-level technical assistance on ...

WFNQASD5

Process Engineer

Anchorage, AK · On-site

Utilize statistical tools such as Minitab and Design of Experiments (DOE) to analyze data and drive ... Process Engineering and Manufacturing Operations expertise enable the engineer to understand and ...

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All JobsData Engineer JobsData Engineer Jobs in Alaska

Data Engineer information

See Alaska salary details

$47.9K

$139.7K

$191.2K

How much do data engineer jobs pay per year?

As of Jul 5, 2026, the average yearly pay for data engineer in Alaska is $139,697.00, according to ZipRecruiter salary data. Most workers in this role earn between $123,300.00 and $148,100.00 per year, depending on experience, location, and employer.

Is a data engineer a difficult job?

A data engineer role involves designing, building, and maintaining data pipelines and infrastructure, which requires strong programming skills, knowledge of databases, and familiarity with tools like SQL, Python, and cloud platforms. The job can be challenging due to the complexity of managing large-scale data systems and ensuring data quality and security, but it is manageable with proper training and experience.

What is the difference between Data Engineer vs Data Scientist?

AspectData EngineerData Scientist
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
SkillsSQL, ETL, programming (Python, Java), database managementStatistics, machine learning, data analysis, programming (Python, R)
Work EnvironmentData warehouses, cloud platforms, backend systemsData analysis environments, research labs, visualization tools
Common ToolsApache Spark, Hadoop, Airflow, SQLJupyter, RStudio, Tableau, scikit-learn

Data Engineers focus on creating and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. Data Scientists analyze this data to generate insights, build predictive models, and support decision-making. While their skills overlap, Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

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

To thrive as a Data Engineer, you need a strong background in computer science, data modeling, and programming languages such as Python or Java, often coupled with a relevant degree. Familiarity with ETL tools, big data frameworks (like Hadoop or Spark), and cloud platforms (such as AWS or Azure) is typically required, along with certifications like AWS Certified Data Analytics. Strong problem-solving skills, attention to detail, and effective communication set exceptional data engineers apart. These skills and qualities are essential for building robust data pipelines, ensuring data quality, and supporting data-driven decision-making across organizations.

What Does a Data Engineer Do?

The job duties of a data engineer involve helping with the development of systems, software, and infrastructure used to process, store and analyze data. Your responsibilities in this career include working to install data management software. Your employer may expect you to perform maintenance and install updates to all software and systems that they use for data acquisition, management, and analysis. Data engineers also analyze existing data systems to find ways to improve efficiency and accessibility. You then suggest upgrades or changes based on your assessment.

What are Data Engineers?

Data Engineers are IT professionals who design, construct, install, and maintain large-scale processing systems and other infrastructure for collecting, storing, and analyzing data. They build and optimize data pipelines and architectures that allow organizations to efficiently access and use data for business insights. Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure that data is reliable, accessible, and secure. Their responsibilities often include working with databases, cloud platforms, and big data tools.

How do Data Engineers typically collaborate with Data Scientists and Analysts within an organization?

Data Engineers play a crucial role in ensuring that Data Scientists and Analysts have reliable, well-structured data for their projects. This collaboration often involves building and maintaining data pipelines, optimizing data storage solutions, and troubleshooting data quality issues. Regular communication and agile teamwork are common, with Data Engineers frequently participating in meetings to understand analytical requirements and adjust data processes accordingly. By working closely together, these teams can quickly iterate on data models and deliver actionable insights to drive business decisions.

What does a data engineer actually do?

A data engineer designs, builds, and maintains the infrastructure and pipelines that enable organizations to collect, store, and process large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible, reliable, and ready for analysis by data scientists and analysts.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior role that requires experience with programming, databases, and data pipelines. Entry-level positions may be available for those with relevant internships, certifications, or strong foundational skills in SQL, Python, or cloud platforms, but most roles expect prior experience or demonstrated technical competence.

What engineer makes $500,000 a year?

Senior data engineers with extensive experience, advanced skills in big data tools, and certifications can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within large tech companies. Such compensation often includes bonuses, stock options, and other incentives. These roles typically require strong programming, cloud platform expertise, and a deep understanding of data architecture.
More about Data Engineer jobs
What are the most commonly searched types of Data Engineer jobs in Alaska? The most popular types of Data Engineer jobs in Alaska are:
What are popular job titles related to Data Engineer jobs in Alaska? For Data Engineer jobs in Alaska, the most frequently searched job titles are:
What job categories do people searching Data Engineer jobs in Alaska look for? The top searched job categories for Data Engineer jobs in Alaska are:
What are popular job titles related to Data Engineer jobs in AK? For Data Engineer jobs in AK, the most frequently searched job titles are:
Data Engineer jobs near you
Infographic showing various Data Engineer job openings in Alaska as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $139,697 per year, or $67.2 per hour.

Technical Architect - Data, Analytics & AI

Munich Re

Anchorage, AK • Hybrid

$65.25 - $83.75/hr

Other

Medical, Life, Retirement, PTO

Posted 29 days ago

Job description

Location: Princeton, New Jersey Hybrid 40-50% onsite 

Role Overview

We are seeking a Technical Architect (TA) with deep expertise in Data, Analytics, and Artificial Intelligence (AI) to join the IT Enterprise Architecture organization. This role is accountable for proactively leading data, analytics, and AIdriven technology transformation initiatives and enabling measurable business outcomes across the enterprise.

The Technical Architect will play a critical role in transforming local, legacy, datadriven processes, and systems into centralized, scalable, and groupwide platforms, while ensuring alignment with enterprise architecture standards and business strategy.

Technical Architects provide technical leadership across analysis, design, facilitation, and execution, supporting the evolution of enterprise Data, Analytics, and AI capabilities and the associated application portfolios and technology stacks. The role owns the creation of key architectural deliverables such as targetstate architectures, transformation roadmaps, standards, and guidelines to enable successful project delivery and longterm strategic outcomes.

This position is based in the USA and ensures that Data, Analytics, and AI architecture vision, principles, and standards are consistently executed through a common enterprise framework, with a strong emphasis on cloudbased data platforms, AI enablement, and data governance.

The ideal candidate will help advance organizational directives around simplification, modernization, and innovation by providing architectural leadership in enterprise data platforms, integration components, and AIenabled data strategies.

Key Responsibilities

  • Assist in the development of a multiyear Data, Analytics, and AI roadmap, aligned with the Munich Re Target Architecture and Roadmap Development Process, in collaboration with Data & Analytics Enterprise Architects.
  • Drive standardization of Data, Analytics, and AI technology standards, principles, and guidelines across multiple business entities.
  • Define and maintain technical standards for enterprise data management, analytics platforms, and AI enablement capabilities.
  • Design and guide datacentric and AIenabled initiatives, supporting the transition from traditional data architectures to nextgeneration cloud, analytics, and AI platforms.
  • Act as an evangelist and ambassador for enterprise architecture standards including Data Governance. Data Intake and Ingestion. Data Modeling, Data Integration, Analytics and AI lifecycle management
  • Collaborate closely with Business Solutions teams, Technology Architects, and Enterprise Data Architects across initiatives and implementations.
  • Identify technologyrelated business pain points by mapping business capabilities to current platforms, leveraging EA practices and participating in innovation activities, including AI adoption.
  • Enable IT development and infrastructure teams to make informed technology decisions through frameworks, reference architectures, standards, and reusable patterns.
  • Identify technical risks, architectural gaps, and vulnerabilities that could impact project delivery or lead to postrelease defects.
  • Reduce cost and complexity through standardization, reuse, and rationalization of data, analytics, and AI platforms.
  • Partner with EA and TA peers (enterprise, solution, and business architects) to derive the futurestate technology architecture, aligned to business strategy and external trends.
  • Define migration and transformation plans to close gaps between current and target states, in alignment with Business Solutions and Business Technology Architects.
  • Support governance, assurance, and compliance activities to ensure alignment with enterprise architecture standards and policies.
  • Assess and articulate the organizational, skills, process, and financial impact of changes to the application portfolio, data platforms, and AI stack.
  • Define and govern enterprise AI architecture standards, including model lifecycle management, MLOps, and AI platform integration.
  • Ensure responsible and compliant AI adoption, aligned with AI governance, model risk management, data privacy, and security controls.
  • Guide the integration of AI/ML capabilities into analytics platforms, including predictive, prescriptive, and generative AI use cases.
  • Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions.
  • Establish architectural patterns for AI model deployment, monitoring, versioning, and retraining in cloud environments.
  • Evaluate emerging AI technologies, tools, and platforms and provide strategic recommendations for enterprise adoption.

 

Your Profile

  • 4+ years of experience in Enterprise Architecture or Technical Architecture.
  • Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, Mathematics, or Business (or equivalent).
  • Strong experience with cloud platforms and services, including:
    • Azure (e.g.; Azure AI Studio, Azure Data Services and tools)
    • AWS  (e.g.; Amazon Bedrock, Sagemaker, Data Services and tools)
    • Databricks
  • Handson experience with enterprise data concepts, including:
    • Data Intake and Ingestion
    • Data Warehousing
    • Data Lakes / Lakehouse architectures
    • ETL / ELT
    • Interactive and operational reporting
    • Statistical and regulatory reporting
    • Master Data Management (MDM)
    • Data Governance, Quality, Security, Audit, Balance & Control
  • Solid understanding of enterprise architecture practices, including:
    • Architectural patterns
    • Roadmaps
    • Architecture Review Boards
    • Solution Design Boards
  • Experience defining data management and AI roadmaps, cloudbased services, and reusable architectural patterns.
  • Experience integrating operational data with enterprise data lakes.
  • Strong understanding of data integration challenges and solution patterns.
  • Experience with statistical and data science languages such as Python and R (strong asset).
  • Exposure to AI/ML concepts, including model development, deployment, monitoring, and MLOps (required).
  • Familiarity with Generative AI concepts, AI platforms, and enterprise adoption considerations (strong asset).
  • Strong business acumen with deep understanding of:
    • Financial systems
    • Corporate and backoffice systems
    • Enterprise data management, analytics, and AI technology landscape
  • Strong problemsolving skills, unquestioned integrity, and high collaboration capability.
  • Passion for innovation, continuous improvement, modernization, and change management.
  • Excellent written and verbal communication skills, with the ability to communicate effectively at all levels.
  • High sense of ownership, accountability, and pride in delivered outcomes.

At Munich Re US, we see Diversity and Inclusion as a solution to the challenges and opportunities all around us. Our goal is to foster an inclusive culture and build a workforce that reflects the customers we serve and the communities in which we live and work. We strive to provide a workplace where all of our colleagues feel respected, valued and empowered to achieve their very best every day. We recruit and develop talent with a focus on providing our customers the most innovative products and services.

We are an equal opportunity employer. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

The Company is open to considering candidates in Princeton, NJ. The salary range posted below applies to the Company's Princeton location.

The base salary range anticipated for this position is $141,800 - $207,900 plus opportunity for company bonus based upon a percentage of eligible pay.  In addition, the company makes available a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, 401k match, retirement savings plan, paid holidays and paid time off (PTO). 

The salary estimate displayed represents the typical salary range for candidates hired in this position in Princeton. Factors that may be used to determine your actual salary include your specific skills, how many years of experience you have and comparison to other employees already in this role. Most candidates will start in the bottom half of the range. 

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