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Data EngineerBlackfoot Telephone Cooperative, Inc. • United States
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Data Engineer

Blackfoot Telephone Cooperative, Inc.
  • US
    United States
  • US
    United States
Apply Now

About

About Us:
Blackfoot Communications reliably connects business of all sizes across the nation using the latest telecommunication technology in voice, network, and managed services. With focus on strong connections, we also provide dedicated account management with a goal to get to know our clients so we can help advise on the best solution.
What We Offer : We offer opportunities in the telecommunications and technology sectors with positions in Western Montana and Eastern Idaho. Blackfoot is proud to offer a competitive salary and a fantastic benefits package that includes; comprehensive medical benefits plan, LTD, life insurance, an outstanding retirement pension plan plus a 401k plan that includes employer match, along with other employer paid benefits. We are proud to have received awards and recognition that highlight our strong company culture. These include "Employer of Choice" from the Missoula Job Service Employer's Council, "Top Tech Employer" from the Montana High Tech Business Alliance, and the "Heart Award" from the United Way of Missoula County in recognition of our ongoing community efforts.
Job Summary:
The Data Engineer designs, builds, and supports data pipelines, transformations, and data products that power enterprise reporting, analytics, and AI workloads. The Data Engineer works closely with the AI & Automation Engineers on shared pipelines, integrations, and orchestration, and provides engineering input and collaboration to the Manager, Digital Intelligence, who owns overall data architecture, modeling standards, and platform direction. The role partners with the Data Governance Committee and business data owners to enforce data quality at ingestion and to keep data accurate, secure, and accessible across the organization.
Essential Job Duties and Responsibilities: Build, maintain, and operate ELT/ETL pipelines between business systems. Develop standardized, reusable data products and curated datasets that replace manually built reports and enable consistent, governed enterprise reporting and analytics. Implement data validation, quality checks, error handling, and reconciliation at ingestion in alignment with Data Governance Committee standards, enforcing data quality at the pipeline rather than in downstream reports. Implement data modeling practices, including dimensional, normalized, and lake house patterns, to structure data for analytics, reporting, and AI workloads. Establish and maintain source control practices for data engineering deliverables Monitor and optimize data platform workloads and data pipelines for reliability, performance, and cost, including warehouse sizing, query tuning, usage patterns, failure modes, and unintended outcomes. Implement and support data ingestion and integration standards including naming conventions, required metadata, refresh cadence, lineage tracking, and audit-ready documentation. Apply security, access controls, and data classification to protect sensitive or regulated data in accordance with internal and regulatory requirements. Partner with business data owners and stewards to translate KPI definitions, business processes, and reporting requirements into reliable, documented datasets and data products. Collaborate closely with the AI & Automation Engineers to align data pipelines, integrations, and orchestration patterns so that data products support automation and AI use cases across corporate, IT, and service provider domains. Execute data transformation and conversion tasks to support operational, analytical, and integration requirements. Provide engineering input and recommendations to the Manager, Digital Intelligence on data architecture, modeling standards, platform direction, and governance approach, and translate those decisions into working pipelines and data products. Provide Tier 2/3 escalation support for data pipeline and data quality issues, focusing on complex problem resolution, root cause analysis, and long-term remediation. Develop automated unit/integration tests and data contracts Additional Job Duties and Responsibilities:
Perform other duties and responsibilities as required to fulfill job function or as assigned.
Knowledge, Skills, and Abilities:
Knowledge of:
Relational and analytical data platforms, including Snowflake Data Platform, SQL Server, and Oracle. Data modeling concepts, including dimensional, normalized, and data vault patterns. ELT and ETL design patterns, including batch, micro-batch, and event-driven ingestion. SQL, Python, and modern data transformation frameworks (e.g. dbt or equivalent). API-based data acquisition standards (REST, JSON, OAuth, webhooks) and event streaming concepts. Telecommunication OSS/BSS data structures, including ServiceNow, Aria, FNT, and billing/financial data domains. Data governance principles including lineage, classification, stewardship, and KPI cataloging. Secure data handling, identity, and access control principles, including protection of regulated and sensitive data. Responsible and governed use of AI tools in data engineering and software engineering contexts. Skill to:
Actively leverage AI-assisted engineering tools in day-to-day development to accelerate pipeline build, improve solution quality, and reduce manual effort, while operating within established security, compliance, and governance standards. Troubleshoot complex cross-system data issues involving ingestion, transformation logic, schema drift, and data synchronization. Translate business reporting and analytics requirements into durable data products and pipeline solutions. Gather and report numerical data and produce and interpret statistical reports. Write original material, edit, proofread, and finalize written material. Operate various office equipment such as a computer, copy machine, fax machine and multi-line telephone. Ability to:
Work independently while collaborating closely with the AI & Automation Engineers, the Manager, Digital Intelligence, and across infrastructure, cybersecurity, and business teams. Function effectively in a fast-paced high-energy department and successfully balance multiple projects in a collaborative environment. Independently solve problems with creativity. Handle multiple priorities, work accurately, work under pressure, and respond quickly to tight deadlines. Speak effectively to individuals and groups of people. Train and teach others. Think analytically and be a problem solver while having a good eye for detail. Communicate effectively, both in writing and in speaking, with customers, co-workers, and various business contacts in a courteous and professional manner. Work completely and accurately under time constraints and deadlines. Read, analyze, and interpret reports. Provide excellent customer service. Work in a safe and effective manner. Maintain confidentiality of Cooperative records when required.
Education and Experience:
Any combination equivalent to the following education and experience that would provide the required knowledge, skills and abilities would qualify. A typical way to obtain the knowledge, skills and abilities would be:
Bachelors' degree in computer science, information systems, management information systems or a related field; 3-5 years of demonstrated equivalent work experience building data pipelines and working with relational databases. Hands-on experience with Oracle and SQL Server in addition to modern cloud data platforms is required, along with proficiency in Python for data engineering work. Familiarity with the telecommunications industry also desired.
Any noted minimum or maximum years of experience should not be construed as a requirement for consideration; this information is meant to be used as a suggested guideline.
  • United States

Languages

  • English
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