Data Analytics Engineer III
AK, United States
GCI
Founded in 1989, GCI is a premier Engineering and Analytics firm with a steadfast commitment to national security and intelligence. Specializing in Data Analytics, Software Development, Engineering,PURPOSE OF POSITION: GCI's Data Analytics Engineer III 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.
- 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:
Requires the ability to perform highly complex and diverse duties under deadlines and constraints. Functions using software engineering principles. Under minimal direction works on more complex projects and processes and a has strong command of scripting languages with the ability to solve complex coding problems. This position is expected to serve as a mentor for junior data engineers and BI analytics team members.
- Oversee the end-to-end analytics lifecycle including data modeling, data preparation and report development. Integrate and manage big data technologies (e.g., Databricks, Spark, Kafka) for real-time data processing and analytics.
- Implement AI driven workflows against data within analytical projects. Build and maintain dashboards and report solutions to monitor network performance, customer behavior, and service quality.
- Guide and mentor junior team members on data engineering best practices, tools, and techniques.
- Work closely with other technical teams (e.g., network engineers, software engineers) to understand business requirements and translate them into data solutions.
Additional Competencies:
- Expertise in SQL, Python, and big data technologies (e.g., Databricks, Spark).
- Strong background in statistics, machine learning, and data analytics, with the ability to apply these skills in a telecommunications context.
- Experience with cloud platforms (e.g., AWS, Azure, GCP) and data storage solutions (e.g., SQL, NoSQL databases).
- Proven ability to lead projects and manage complex data analytics initiatives.
- Experience with ETL processes, data pipeline design, and data warehousing.
- Strong understanding of telecommunications data, network architecture, and key performance metrics.
- Experience with spatial data analysis, map creation and geographic data visualization.
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, Software/Computer Engineering, or relevant field.*
- Minimum of six (6) years’ experience in data engineering, analytics engineering, or a related role in the telecommunications industry. *
Preferred:
- Experience with real-time data processing and streaming technologies (e.g., Kafka, Apache Flink).
- 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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture AWS Azure Big Data Classification Computer Science CX Data analysis Data Analytics Databricks Data pipelines Data quality Data visualization Data warehouse Data Warehousing Engineering ETL Excel Flink GCP Google Cloud Kafka Machine Learning NoSQL PhD Pipelines Power BI Python R Security Spark SQL Statistics Streaming Tableau
Perks/benefits: Career development Gear
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