Data Engineer - Telecommuncations

Hamilton Barnes Associates Limited; United States; On-site; USD 140,000 - 155,000; Full time

Job summary

Hamilton Barnes Associates Limited is seeking a Data Engineer to design, build, and maintain a cloud data platform that supports analytics, reporting, automation, and AI-driven applications. The role emphasizes enterprise data architecture, data integration, scalable models, and secure, reliable data workloads.

The candidate will model geospatial data, support RAG and AI workloads, and collaborate with IT, Security, and stakeholders to translate operational needs into scalable data solutions

Qualifications

• Bachelor's degree or equivalent practical experience
• 3–6 years of data engineering experience with enterprise data warehouses and scalable analytical models
• Strong SQL and data modeling principles
• Hands-on with Snowflake/BigQuery/Redshift or similar
• Proficient in Python for data integration and pipelines
• Experience with geospatial data and Azure data services
• Able to own and deliver data solutions in a fast-paced environment
• Excellent communication with stakeholders

Responsibilities

• Design scalable cloud-based data models integrating multiple data sources
• Develop and maintain ingestion, transformation, orchestration, and monitoring processes
• Create and optimize data warehouses, marts, and analytical datasets for analytics and AI workloads
• Model and manage geospatial data and location-based relationships
• Structure data to support RAG, AI search, analytics and ML
• Establish data quality, governance, lineage, and confidentiality standards
• Collaborate with IT, Security, and Infrastructure for access controls and reliability
• Partner with stakeholders to translate requirements into scalable data solutions
• Monitor and optimize data platform performance and cost
• Utilize AI-powered tools to enhance productivity and outcomes

Skills

SQL

Data modeling

Python

Geospatial data

Azure data services

Data integration

Stakeholder communication

Education

Bachelor's degree in CS/IS/Data Eng or related

Tools

Snowflake

BigQuery

Redshift

dbt

Airflow

Azure Data Factory

Dagster

Esri ArcGIS

Job description

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.

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