Data Engineer

Metronet is one of the nation’s fastest-growing fiber-optic companies, focused on building communities through connectivity. As a Data Engineer, you will design and optimize data infrastructure and pipelines to support business intelligence and analytics initiatives, ensuring data reliability and accessibility.

Responsibilities:

• Design and develop data serving and semantic layers to support business needs ranging from traditional reporting to reverse ETL and LLM/AI implementations
• Develop data models for use by analysts and applications from across the business using modern dimensional modeling practices to efficiently serve accurate, consistent data
• Build and maintain robust, scalable data pipelines to extract, transform, and load (ETL, ELT) data from various sources into the data platform using both batch processing and event-driven patterns
• Create efficient, performant data models to support business requirements and analytics needs
• Implement and automate data quality checks and monitoring to ensure data accuracy and drive observability
• Manage, troubleshoot and optimize existing data infrastructure, including cloud-based solutions and on-premises systems
• Leverage cloud data platforms (Fabric, Databricks, Snowflake, etc.) for data storage, processing, and analysis
• Work closely with data analysts, data scientists, and business stakeholders to understand their data needs and deliver solutions
• Identify and resolve data-related issues and challenges for technical and non-technical stakeholders
• Support company-wide projects ranging from server migrations to mergers and acquisitions as a data and systems expert
• Automate data processes to improve efficiency and reduce manual effort. Implement modern concepts like metadata-driven pipelines and Infrastructure-as-Code that will play a key role in a scalable, resilient data platform
• Document data processes, architecture, and workflows
• All other duties as assigned

Requirements:

• Bachelor's degree in computer science, engineering, or a related field
• Advanced SQL skills required, experience with the use of programming languages (Python, Java, Scala) preferred
• Experience with data warehousing and data lake technologies, concepts and best practices
• Experience with and understanding dimensional modeling concepts and best practices
• Understanding of data modeling and ETL processes and best practices
• Experience with cloud platforms (Azure, AWS, etc.) is required; experience with data platforms like Fabric, Databricks or Snowflake is preferred
• Strong analytical and problem-solving skills
• Willingness to work as a team and independently
• Must be legally authorized to work in the U.S
• 3 – 5 years of experience as a Data Engineer or Analytics Engineer
• Experience with Spark (PySpark, SQL SQL, etc.)
• Experience with developing bespoke data pipelines and handling various authentication patterns
• Experience with the use of programming languages (Python, Java, Scala) preferred
• Experience with data platforms like Fabric, Databricks or Snowflake is preferred