Senior Data Engineer

April 2

🥔 Idaho – Remote

Although this job is listed in Idaho, this company may be open to hiring remote in other states.

🦬 Montana – Remote

Although this job is listed in Montana, this company may be open to hiring remote in other states.

+2 more states

🥔 Idaho – Remote 🦬 Montana – Remote 🌲 Oregon – Remote ☕ Washington – Remote

💵 $114.7k - $154.2k / year

⏰ Full Time

🟠 Senior

🚰 Data Engineer

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Ziply Fiber

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Ziply Fiber is a leading provider of fiber-optic internet services in the Pacific Northwest, offering high-speed internet plans that cater to both residential and business customers. With a focus on transparency and customer satisfaction, Ziply Fiber provides no annual contracts, no data caps, and a variety of multi-gig internet options designed for modern households and businesses. Their services include whole home WiFi, streaming TV, and phone services, making them a one-stop solution for connectivity needs.

1001 - 5000 employees

Founded 2020

📡 Telecommunications

👥 B2C

💰 Corporate Round on 2022-11

📋 Description

• The Senior Data Engineer will be responsible for designing, building, and maintaining scalable data pipelines, data models, and infrastructure that support business intelligence, analytics, and operational data needs. • This role involves working with various structured and unstructured data sources, optimizing data workflows, and ensuring high data reliability and quality. • The ideal candidate will be proficient in modern data engineering tools and cloud platforms bringing innovative solutions to a fast-paced and diverse data infrastructure. • Essential Duties and Responsibilities: • Design, develop, and maintain scalable data pipelines for ingestion, transformation, and storage of large datasets. • Optimize data models for analytics and business intelligence reporting. • Build and maintain data infrastructure, ensuring performance, reliability, and scalability. • Collaborate with data analysts, data scientists, and business stakeholders to understand data needs and design appropriate solutions. • Implement best practices for data governance, security, and compliance. • Work with structured and unstructured data, integrating data from various sources including databases, APIs, and streaming platforms. • Troubleshoot and resolve data pipeline and ETL failures, implementing robust monitoring and alerting systems. • Automate data workflows to increase efficiency and reduce manual intervention. • Mentor and train junior engineers, fostering a culture of learning and innovation. • Develop and maintain documentation for data engineering processes and workflows.

🎯 Requirements

• A Bachelor’s degree in Computer Science, Engineering, or a related field is required • Minimum of eight (8) years of experience in data engineering, ETL development, or related fields • Strong proficiency in SQL and database technologies (PostgreSQL, MySQL, Oracle, SQL Server, etc.) • Experience with big data processing frameworks such as Spark, Hadoop, Flink, and Apache Hudi • Familiarity with Linux/Unix and scripting technologies utilized on them • Proficiency in programming languages such as Python, Java, or Scala for data engineering tasks • Hands-on experience with cloud platforms such as Microsoft Azure and its data services such as Azure Data Factory, Azure Synapse Analytics, and Azure Databricks • Experience working with data warehouses such as Snowflake, Redshift, BigQuery, or Azure SQL Data Warehouse • Familiarity with workflow orchestration tools such as Apache Airflow or Azure Data Factory • Knowledge of data modeling, schema design, and data architecture best practices • Strong understanding of data governance, security, and compliance standards • Ability to work independently in a remote environment and collaborate effectively across teams • Experience with Infrastructure as Code (IaC) tools such as Terraform, CloudFormation, or Azure Resource Manager (ARM) templates • Knowledge of containerization and orchestration technologies such as Docker, Kubernetes, and Azure Kubernetes Service (AKS) • Exposure to GraphQL and RESTful APIs for data retrieval and integration • Familiarity with NoSQL databases such as MongoDB, DynamoDB, Cassandra, or Azure Cosmos DB • Experience required with: real-time analytics databases such as Apache Pinot. • data transformation tools such as DBT, AWS Glue, or Alteryx. • metadata management and data discovery tools such as Apache DataHub. • Data visualization tools such as Tableau, Power BI, or Looker. • version control software such as GitLab.

🏖️ Benefits

• Comprehensive health benefits include - medical, dental, vision, 401k, flexible spending account, paid sick leave and paid time off • parental leave • quarterly performance bonus • training • career growth and education reimbursement programs