Senior Data Engineer, Telecom EDW

Major Duties

Position may be located remote. #LI-Remote

Fidium is where next-generation fiber meets next-level opportunity. With a vision to be America's favorite fiber internet and network services provider, we deliver lightning-fast and reliable connections to families, businesses, and communities.

Backed by one of the nation's top 10 fiber networks, Fidium is driven by a team of 2,500 employees. We champion innovation, integrity, and continuous improvement—empowering every team member to make a meaningful impact.

We are seeking a skilled Data Engineer to support our Telecom Enterprise Data Warehouse (EDW) environment. The ideal candidate will have strong hands-on experience in data ingestion, transformation, data quality assurance, operations engineering, data modeling, and data delivery, working within a modern cloud data stack leveraging Five Tran, Snowflake, Matillion, Tableau, and Secoda.

This role plays a key part in ensuring the availability, reliability, and quality of data that powers enterprise analytics, reporting, and strategic decision-making across the telecom organization.

Data Ingestion & Integration

• Design, implement, and manage automated data ingestion pipelines using Five Tran and other ETL/ELT tools.
• Integrate data from various telecom systems (OSS/BSS, CRM, billing, network systems, etc.) into Snowflake.
• Ensure scalability and reliability of data ingestion processes to meet business SLAs.

Data Transformation & Modeling

• Develop and optimize ELT pipelines in Matillion, ensuring efficient data transformations in Snowflake.
• Build and maintain data models (staging, core, mart layers) to support reporting and analytics needs.
• Follow and enforce data modeling best practices, ensuring consistent naming, lineage, and documentation across datasets.

Data Quality & Governance

• Implement and monitor data validation, profiling, and quality checks to ensure data accuracy, completeness, and timeliness.
• Collaborate with data governance teams to maintain metadata, lineage, and documentation within Secoda.
• Troubleshoot and resolve data discrepancies and pipeline failures proactively.

Operations Engineering

• Support daily operations of the EDW, including job scheduling, monitoring, and performance tuning.
• Implement alerting, logging, and observability practices to ensure high system uptime.
• Participate in on-call rotations or provide after-hours support as needed.

Analytics & Data Delivery

• Partner with analysts, BI developers and business stakeholders to enable data consumption in Tableau and other downstream systems.
• Develop and optimize data extracts, dashboards, and APIs for business use cases.
• Ensure alignment between data warehouse design and analytical/reporting requirements.

Collaboration & Continuous Improvement

• Work closely with data architects, business analysts, and domain experts to translate business needs into data engineering solutions.
• Contribute to standards, best practices, and automation within the data engineering team.

Support continuous improvement of ETL/ELT frameworks, CI/CD pipelines, and Dev Ops processes.

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related field.
• 8+ years of experience in data engineering or data warehousing, preferably in the telecom domain.
• Strong proficiency with:
• Five Tran (data ingestion and connector management)
• Snowflake (SQL, warehouse configuration, performance optimization)
• Matillion (ELT orchestration and transformation development)
• Tableau (understanding of data delivery and visualization integration)
• Secoda (data cataloging and lineage documentation) or similar solution
• Solid understanding of data modeling (star/snowflake schemas, dimensional modeling).
• Experience with data quality frameworks, metadata management, and Dev Ops for data pipelines.
• Strong SQL skills and familiarity with Python or bash scripting for automation.
• Experience with cloud environments (AWS, Azure, or GCP).

Preferred Qualifications:

• Telecom industry experience, particularly with OSS/BSS and network data sources.
• Experience in CI/CD for data pipelines (Git, Jenkins, or similar).
• Familiarity with dbt or similar data transformation…