Data Analytics Engineer

Zayo•Denver, CO

15h•Hybrid

About The Position

Zayo is seeking an experienced Data Analytics Engineer to join their Network Data Solutions team. This role involves combining deep telecom data expertise with technical skills to design and deliver high-quality data products. The engineer will collaborate with network operations, engineering, and technology partners to understand needs, document requirements, and translate them into scalable data solutions. Responsibilities include analyzing existing processes and data pipelines to identify improvements, and proposing innovative solutions to enhance network performance, reliability, and operational efficiency. The role requires end-to-end development using expertise in data design, data engineering (ETL/ELT), and business intelligence.

Requirements

Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, Telecommunications, or a related field (or equivalent experience).
Minimum of five (5) years of experience in analytics engineering, data engineering, or BI roles — preferably supporting telecom or network operations.
Strong proficiency in SQL, Snowflake, dbt, and Python for data transformation and automation.
Hands-on experience with Azure Data Factory and Microsoft Fabric for pipeline orchestration and data lakehouse management.
Advanced experience building and optimizing Power BI, Sigma and/or Tableau dashboards.
Deep understanding of telecom data domains, including (examples you can customize): 1) Network inventory and topology systems (e.g., NMS, OSS, GIS); 2) Fault, performance, and capacity management data; 3) Provisioning, activation, and service assurance systems
Proven ability to analyze complex business problems, identify gaps in existing processes, and propose scalable data solutions.
Strong communication and documentation skills, with the ability to bridge business and technical perspectives.
US Citizenship or an existing Green Card.

Nice To Haves

Familiarity with CI/CD tools (e.g., GitHub, Azure DevOps).
Experience implementing data quality frameworks and metadata management practices.
Background in network engineering analytics, service performance monitoring, or customer experience analytics.
Knowledge of telecom industry KPIs and metrics (e.g., uptime, MTTR, capacity utilization, throughput, etc.).

Responsibilities

Partner with network and technology stakeholders to understand business objectives, challenges, and data requirements across areas such as network performance, reliability, capacity, and customer experience.
Develop and maintain deep knowledge of telecom data domains and source systems, including network inventory, provisioning, assurance, fault, and performance data.
Lead the creation of BTS (BRD Technical Specification) documentation, translating business logic into clear technical solutions.
Design, build, and maintain robust data products that support operational and strategic reporting — from ingestion through transformation, modeling, and visualization.
Evaluate existing data processes and models to identify opportunities for standardization, optimization, and automation.
Propose and implement innovative solutions that improve data accessibility, quality, and usability for network teams.
Develop scalable data models using dbt and Snowflake aligned to modern data architecture principles.
Build and orchestrate ETL/ELT pipelines in Azure Data Factory and Microsoft Fabric, ensuring efficiency and reliability.
Write and optimize SQL and Python code for advanced data manipulation, automation, and validation.
Facilitate UAT (User Acceptance Testing) with business partners to ensure data solutions align with real-world operational needs.
Design and deliver dashboards and reports using Power BI, Sigma, and Tableau that translate complex network data into actionable insights.
Collaborate with data engineers, analysts, and architects to maintain alignment across the broader data ecosystem.
Serve as a subject matter expert (SME) for network-related data and analytics, mentoring others on telecom-specific concepts, sources, and logic.