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Manager Data Analytics Engineer Jobs in Alaska (NOW HIRING)

Revenue cycle management (R30/60/90 aging, collections, forecasts) * Clinic-level and regional ... Required Skills & Experience * 8+ years of hands-on experience in data analytics or engineering

Data Analyst

Anchorage, AK · On-site

$1.5K - $2.0K/yr

Knowledge of database management systems and SQL. Responsibilities: * Collect, clean, and ... Utilize statistical tools and programming languages such as R and SAS to perform data analysis and ...

Data Analyst

Anchorage, AK · On-site

$71K/yr

Promote best practices in data management, including standardizing definitions, metrics and ... Minimum 3 years of experience in data analytics, business intelligence, or financial analysis.

$100/hr

Bachelor's degree in a quantitative or technical field preferred. * 3-5 years of experience in a data analytics, data engineering, or BI analyst role. * Proven ability to build and manage data ...

Data Analyst

Anchorage, AK · On-site

$12.10/hr

Analytics/ Consulting/Communicating: * Work with Business Unit champions and Subject Matter Experts ... Excellent project management skills * Strong verbal and interpersonal skills, with demonstrated ...

Support, promote, and document all Data Management processes and procedures. * Develop workflows ... Strong analytical and problem-solving skills. * Proficiency in data management tools and software.

Launched by Management Consultants, our multidisciplinary teams bring together the talents of ... Bachelor's in Engineering, Data Analytics, Business, or Environmental Science; 5-8 years experience;

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Manager Data Analytics Engineer information

What is the difference between Manager Data Analytics Engineer vs Data Analytics Engineer?

AspectManager Data Analytics EngineerData Analytics Engineer
Required CredentialsBachelor's or Master's in Data Science, Analytics, or related field; often leadership experienceBachelor's or Master's in Data Science, Analytics, or related field
Work EnvironmentLeads teams, manages projects, collaborates with stakeholdersDevelops data models, analyzes data, implements solutions
Employer & Industry UsageUsed in tech, finance, healthcare, and large enterprisesCommon in similar industries, often within data teams

The main difference is that a Manager Data Analytics Engineer oversees teams and projects, focusing on leadership and strategic planning, while a Data Analytics Engineer primarily develops and implements data solutions. Both roles require strong technical skills, but the manager role adds a layer of team management and stakeholder communication.

How does a Manager Data Analytics Engineer typically balance technical project work with team leadership responsibilities?

As a Manager Data Analytics Engineer, you are expected to split your time between overseeing complex analytics engineering tasks and guiding your team’s development. This involves setting project priorities, conducting code reviews, and ensuring data solutions align with business goals, while also mentoring team members and facilitating collaboration with stakeholders like data scientists and business analysts. Successful managers often establish clear communication channels and delegate tasks effectively, so they can stay hands-on with key projects while supporting the professional growth of their team.

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

To thrive as a Manager Data Analytics Engineer, you need a strong background in data engineering, analytics, and leadership, typically with a degree in computer science or a related field. Familiarity with tools like SQL, Python, data warehousing platforms (e.g., Snowflake, Redshift), and certifications in cloud technologies or data management are common requirements. Excellent communication, problem-solving, and team management skills set top performers apart in this role. These competencies are essential for driving data strategy, ensuring data quality, and leading analytics teams to deliver actionable business insights.

What is a Manager Data Analytics Engineer?

A Manager Data Analytics Engineer is a professional who leads a team of data analytics engineers responsible for designing, building, and maintaining data systems and analytics solutions. They oversee data pipeline development, ensure data quality, and collaborate with stakeholders to translate business requirements into technical solutions. In addition to technical expertise, they manage project timelines, mentor team members, and help drive data-driven decision-making across the organization.
What are popular job titles related to Manager Data Analytics Engineer jobs in Alaska? For Manager Data Analytics Engineer jobs in Alaska, the most frequently searched job titles are:
What job categories do people searching Manager Data Analytics Engineer jobs in Alaska look for? The top searched job categories for Manager Data Analytics Engineer jobs in Alaska are:
What cities in Alaska are hiring for Manager Data Analytics Engineer jobs? Cities in Alaska with the most Manager Data Analytics Engineer job openings:
Infographic showing various Manager Data Analytics Engineer job openings in Alaska as of June 2026, with employment types broken down into 82% Full Time, 12% Part Time, 2% Temporary, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
Data Analytics Engineer I (Future Opening)

Data Analytics Engineer I (Future Opening)

GCI

Anchorage, AK

$118K - $142K/yr

Full-time

Posted 9 days ago


Job description

This posting is to gather interest for the Data Analytics Engineer I. We are not currently hiring, but will be contacting candidates when we have an opening.

GCI's Data Analytics Engineer I will be responsible for designing, developing, and maintaining  interactive dashboards and reports that support data driven decision making within the organization. This hybrid role combines the functions of data engineering and analytics engineering, enabling the organization to leverage large-scale data for actionable business insights. Position will collaborate with cross-functional teams to ensure the quality, efficiency, and scalability of data while providing advanced analytics solutions to enhance network performance, customer experience, and operational efficiency.

ESSENTIAL DUTIES AND RESPONSIBILITIES AT ALL LEVELS:

Analytics Engineering:

  • Develop and implement data models, algorithms, and analytical solutions to derive insights from large datasets, including network performance analysis, customer behavior modeling, churn prediction, and operational optimization.
  • Implement AI driven workflows against data within analytical projects. Create automated reporting and visualization tools (e.g., dashboards, KPI reports) to communicate insights to stakeholders and drive data-informed decision-making.
  • Collaborate with business units to understand analytical needs and translate them into actionable data solutions.

Data Engineering:

  • Design, develop, and maintain robust data pipelines that efficiently collect, process, and transform data from various telecommunications sources (e.g., network performance, customer usage data, call data records, billing systems).
  • Implement and manage ETL (Extract, Transform, Load) processes to ensure seamless integration of data from multiple systems into a centralized data warehouse or data lake.
  • Ensure data quality and integrity by identifying, resolving, and preventing data discrepancies and errors.
  • Optimize and streamline data storage and retrieval processes to support real-time and batch data analysis needs.

Cross-Functional Collaboration:

  • Work closely with data scientists, business analysts, and IT teams to design and implement visualizations that provide meaningful insights.
  • Provide technical guidance and support to junior team members and other departments in data-related initiatives.

Continuous Improvement & Innovation:

  • Stay up to date with the latest trends and technologies in data engineering, analytics, and telecommunications.
  • Identify opportunities to improve existing data systems, pipelines, and analytics models to drive greater efficiency and business impact.
  • Contribute to the development and adoption of new data technologies, methodologies, and best practices within the organization.
COMPETENCIES:
  • ACCOUNTABILITY- Takes ownership for actions, decisions, and results; openly accepts feedback and demonstrates a willingness to improve.
    • Take ownership and accountability of problems and facilitate finding a solution, involving other groups as necessary. 
    • Own and manage priorities and individual tasks without direct supervision.
    • Take the initiative and seek out opportunities. Assess and accept risks and learn from mistakes. 
  • BASIC PRINCIPLES - Interacts with people in a way that builds mutual trust, confidence, and respect; adheres to GCI's Code of Conduct for Employees - the Basic Principles.
    • Lead by example on all fronts.
    • Guide development teams in a manner that creates success and allows for future self-sufficiency.
  • Foster innovation and promote teamwork.
  • COLLABORATION - Works effectively with others to accomplish common goals and objectives; maintains positive relationships even under difficult circumstances.
    • Build and maintain effective working relationships with leadership, peers, customers, and vendors. Work to resolve problem relationships directly.
  • COMMUNICATION- Conveys thoughts and expresses ideas appropriately and professionally.
    • Build and maintain effective working relationships with leadership, peers, customers, and vendors.
    • Work to resolve problem relationships directly. 
    • Create clear and concise written documentation for a variety of audiences, including developers, business analysts and business users. 
  • COMPLIANCE - Follows internal controls; protects company and customer confidential information; abides by GCI's Code of Business Conduct & Ethics.
  • Reviews modules for quality assurance.
  • CUSTOMER FOCUS - Demonstrates commitment to service excellence; gives high priority to customer satisfaction. 
    • Provide a professional level of service to both external and internal customers. 
  • RELIABILITY - Consistently follows through on assigned tasks as expected; demonstrates timely attendance at meetings, training, and other work obligations.
  • RESULTS - Uses a combination of knowledge, initiative, sound decision making, innovation, adaptability, and problem solving.
  • SAFETY & SECURITY - Supports a safe work environment by following all workplace safety rules and guidelines; complies with applicable Security policies and procedures.
  • TECHNICAL COMPETENCIES -
    • MS Office knowledge (e.g., Outlook, Teams, Word, Excel). Ability to Design, Evaluate, and test data infrastructure.
    • Proficiency in SQL, Python, and R for data manipulation and analytics.
    • Experience with big data technologies (e.g., Spark, Databricks) and cloud platforms (AWS, Azure, Google Cloud).

Proficient with data visualization tools (e.g., Tableau, Power BI).

  • Knowledge of machine learning algorithms and statistical analysis techniques.
  • Familiarity with telecommunications systems and related data types (e.g., network performance metrics, call data records).

Additional Job Requirements:

Works under moderate supervision, supports the team with reasonably complex issues, processes and projects developing a stronger working knowledge of subject matter. 

  • Assist in the collection, processing, and cleaning of raw data from various sources (e.g., network performance, customer usage data, billing systems).
  • Develop and maintain  dashboards and reports.
  • Write basic SQL queries to query and extract data for analysis.
  • Assist senior team members with data preparation tasks, including data validation and transformation.
  • Conduct basic exploratory data analysis (EDA) and assist in visualizing data for team reports.
  • Document data processes and workflows to maintain clarity on pipeline structures and operational processes.

Additional Competencies:

  • Familiarity with SQL, Python, and data visualization tools (e.g., Tableau, Power BI).
  • Ability to collaborate with cross-functional teams.
  • Eagerness to learn and develop technical skills in data engineering and analytics.
  • Basic understanding with ETL processes, data pipeline design, and data warehousing.
  • Basic understanding of telecommunications systems, data, network architecture, and key performance metrics.
  • Familiarity with spatial data analysis.

Minimum Qualifications:

Required: *A combination of relevant work experience and/or education sufficient to perform the duties of the job may substitute to meet the total years required on a year-for-year basis

  • High School diploma or equivalent.
  • Bachelor's degree in Computer Science, Data Science, Engineering, Telecommunications, or a related field. *
  • Minimum of one (1) year of experience in data engineering, analytics engineering, or a related role in the telecommunications industry. *

Preferred:

  • Advanced degree (Master's or PhD) in Data Science, Machine Learning, or a related field.
  • Familiarity with network optimization, customer experience analysis, or predictive analytics in telecommunications.
  • Other telecom industry or job specific certifications. 

DRIVING REQUIREMENTS: 

This position may require access to reliable transportation for occasional travel, such as between retail store locations, offices, worksites, or other locations as needed. 

PHYSICAL REQUIREMENTS and WORKING CONDITIONS:  
  • Work is primarily sedentary, requiring daily routine computer usage.
  • Ability to work shifts as assigned, work in standard office/home office setting, and operate standard office equipment.
  • Ability to accurately communicate information and ideas to others effectively.
  • Physical agility and effort sufficiently to perform job duties safely and effectively.
  • Ability to make valid judgments and decisions.  
  • Available to work additional time on weekends, holidays, before or after normal work hours when necessary. 
  • Must work well in a team environment and be able to work with a diverse group of people and customers. 
  • Virtual workers must comply with remote work policies and agreements.
The company and its subsidiaries operate in a 24/7 environment providing critical services to Alaskans and may need to respond to public health and safety matters or other business emergencies. Due to business needs employees may be contacted outside of the core business hours to respond to an immediate emergency. As such, you will be requested to provide emergency after hours contact numbers, to include your home and cell phone numbers if you have those services. Culture, Engagement, and Connection: At GCI, we foster an environment where the unique perspectives of our employees, customers, and fellow Alaskans are celebrated. We add value to our community by nurturing and empowering each member of our workforce, ensuring equal opportunities for every Trailblazer. EEO: GCI is an equal opportunity employer. Qualified applicants are considered for employment without regard to race, color, religion, national origin, age, sex, sexual orientation, gender identity, marital status, mental or physical disability, veteran status, or any other status or classification protected under applicable state or federal law.  DISCLAIMER:  The above information in this description has been designed to indicate the general nature and level of work performed by employees within this classification.  It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities, and qualifications required of employees assigned to this job. All employees of GCI work in support of the GCI Mission Statement and Declaration of Principles which are located on the GCI Career page and Employee portal.