Data Engineer - Telecommuncations

Keen to join a company that champions growth and development?

Join a leading provider of fibre-based broadband services, delivering multi-gigabit connectivity, Ethernet, dark fibre, and fibre optic and wireless infrastructure solutions across the United States. The organisation is focused on expanding a large-scale open-access fibre network to provide fast, reliable, high-capacity connectivity nationwide.

This company is looking for a Data Engineer to design, build, and maintain the cloud data platform supporting analytics, reporting, automation, and AI-driven applications. The role involves shaping enterprise data architecture, integrating operational data sources, developing scalable data models, and ensuring data is accessible, reliable, secure, and AI-ready.

Don’t miss out on this exciting opportunity and apply today!

Responsibilities:

• Design and build scalable cloud-based data models that integrate operational, financial, engineering, and field data into reliable and queryable data assets. 
• Develop and maintain data ingestion, transformation, orchestration, and monitoring processes across multiple source systems. 
• Create and optimize enterprise data warehouses, marts, and analytical datasets that support reporting, analytics, and AI workloads. 
• Model and manage geospatial data, including spatial data types, coordinate systems, and location-based relationships. 
• Structure data to support retrieval-augmented generation (RAG), AI search, analytics, and machine learning applications. 
• Establish and maintain standards for data quality, governance, lineage, documentation, and confidentiality. 
• Partner with IT, Security, and Infrastructure teams to ensure appropriate access controls, reliability, and platform performance. 
• Collaborate with business stakeholders to translate operational requirements into scalable data solutions. 
• Monitor and optimize data platform performance, reliability, and cost efficiency. 
• Utilize AI-powered tools to improve productivity and accelerate data engineering outcomes. 

Skills/Must Have:

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, Engineering, Mathematics, or a related discipline, or equivalent practical experience. 
• 3 to 6 years of experience in data engineering with demonstrated success designing and building enterprise data warehouses, business-focused data marts, and scalable analytical data models
• Strong proficiency in SQL and data modeling principles. 
• Hands-on experience with cloud data warehouse platforms such as Snowflake, BigQuery, Redshift, or similar technologies. 
• Strong proficiency in Python for data integration, transformation, and pipeline development. 
• Experience working with geospatial data, spatial data types, projections, and location-based analysis. 
• Experience with cloud platforms, preferably Microsoft Azure, including storage, data pipelines, and serverless technologies. 
• Ability to independently own and deliver data engineering solutions in a fast-paced environment. 
• Strong communication skills and the ability to partner effectively with technical and non-technical stakeholders. 
• Strong analytical, problem-solving, and critical-thinking skills. 

Desirable Skills:

• Experience with dbt or similar data transformation frameworks. 
• Experience with orchestration technologies such as Airflow, Azure Data Factory, Dagster, or comparable platforms. 
• Familiarity with geospatial or OSP platforms such as Esri and ArcGIS. 
• Experience preparing, modeling, and optimizing data for AI, machine learning, and retrieval-augmented generation (RAG) use cases. 
• Experience handling confidential, sensitive, or regulated operational data environments. 
• Data Architecture & Modeling: Designs scalable, maintainable, and high-quality data structures that support enterprise decision-making. 
• Data Platform Engineering: Builds reliable, secure, and performant data solutions that enable analytics and AI innovation. 
• Operational Excellence: Establishes standards for quality, governance, monitoring, and continuous improvement. 
• Business Partnership: Collaborates with stakeholders to translate operational needs into valuable data assets. 
• Problem Solving & Analysis: Uses data-driven thinking to address complex business and technology challenges. 
• Innovation & Automation: Continuously seeks opportunities to improve efficiency through modern data technologies and automation. 
• Ownership & Accountability: Takes end-to-end responsibility for delivering high-impact data solutions. 

Salary:

• $140k - $155k