Data Engineer

Ziply Fiber
  • Kirkland, WA
    3 days ago

    Job Description

    Position Title: Data Engineer
    Base Salary: $101,800 to $142,300 annually DOE
    Benefits: 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.

    Ziply Fiber is a local internet service provider dedicated to elevating the connected lives of the
    communities we serve. We offer the fastest home internet in the nation, a refreshingly great customer
    experience, and affordable plans that put customers in charge.
    As our state-of-the-art fiber network expands, so does our need for team members who can help us grow
    and realize our goals.

    Our Company Values:

    Genuinely Caring: We treat customers and colleagues like neighbors, with empathy and full
    attention.
    Empowering You: We help customers choose what is best for them, and we support
    employees in implementing new ideas and solutions.
    Innovation and Improvement: We constantly seek ways to improve how we serve customers
    and each other.
    Earning Your Trust: We build trust through clear, honest, human communication.

    Job Summary
    The 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:

    The Essential Duties and Responsibilities listed below are a range of duties performed by the employee
    and not intended to reflect all duties performed.

    Data Pipeline Development and Integration
    • Design, develop, and maintain scalable data pipelines for ingestion, transformation, and
    storage of large datasets.
    • Work with structured and unstructured data, integrating data from various sources including
    databases, APIs, and streaming platforms.

    Data Modeling, Analytics, and Infrastructure
    • Optimize data models for analytics and business intelligence reporting.
    • Build and maintain data infrastructure, ensuring performance, reliability, and scalability.

    Operational Excellence, Automation, and Documentation
    • Troubleshoot and resolve data pipeline and ETL failures, implementing robust monitoring and
    alerting systems.
    • Automate data workflows to increase efficiency and reduce manual intervention.
    • Develop and maintain documentation for data engineering processes and workflows.

    Stakeholder Collaboration, Governance, and Compliance
    • 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.

    Other Duties
    • Performs other duties as required to support the business and evolving organization.

    Required Qualifications:
    • Bachelor’s degree in computer science, Engineering, or a related field.
    • Minimum of three (3) 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.
    • Proficiency in programming languages such as Python, Java, or Scala for data engineering tasks.
    • Hands-on experience with cloud platforms, with a strong focus on 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 with:
    o Real-time analytics databases such as Apache Pinot.
    o Data transformation tools such as DBT, AWS Glue, or Alteryx.
    o Metadata management and data discovery tools such as Apache DataHub.
    o Data visualization tools such as Tableau, Power BI, or Looker.
    o Version control software such as GitLab.

    Knowledge, Skills, and Abilities:
    • Experience working with real-time data streaming technologies like Kafka, Kinesis, or Azure
    Event Hubs.
    • Knowledge of machine learning pipelines and MLOps best practices, with experience using Azure
    Machine Learning.
    • Familiarity with DevOps practices and CI/CD pipelines for data engineering, including Azure
    DevOps.
    • Understanding of data privacy regulations such as GDPR and CCPA.

    Work Authorization
    Applicants must be currently authorized to work in the US for any employer. Sponsorship is not available
    for this position.

    Physical Requirements
    The physical demands described here are representative of those that must be met by an employee to
    successfully perform the essential functions of this job. Reasonable accommodations may be made to
    enable individuals with disabilities to perform the essential functions.

    Essential and marginal functions may require maintaining physical condition necessary for bending,
    stooping, sitting, walking, or standing for prolonged periods of time; most of time is spent sitting in a
    comfortable position with frequent opportunity to move about. The employee must occasionally lift and/or
    move up to 25 pounds. Specific vision abilities required by the job include close vision, distance vision,
    color vision, peripheral vision, depth perception, and the ability to adjust focus.

    Work Environment
    Work is performed in an office setting with exposure to computer screens and requires extensive use of a
    computer, keyboard, mouse, and multi-line telephone system. The work is primarily a modern office
    setting.

    At all times, Ziply Fiber must be your primary employer. Unless otherwise prohibited by law, employees
    may not hold outside employment nor be self-employed without obtaining approval in writing from Ziply
    Fiber. In holding outside employment or self-employment, employees should ensure that participation
    does not conflict with responsibilities to Ziply Fiber or its business interests.

    Diverse Workforce / EEO:
    Ziply Fiber is an equal opportunity employer. Ziply Fiber will consider all qualified candidates regardless of
    race, color, religion, national origin, gender, age, marital status, sexual orientation, veteran status, and the
    presence of a non-job-related handicap or disability or any other legally protected status.

    Ziply Fiber requires a pre-employment background check as conditions of employment. Ziply Fiber may
    require a pre-employment drug screening.

    Ziply Fiber is a drug free workplace.


    Numbers & Facts

    LocationKirkland, WA

    Skills

    • ARM (Advanced RISC Machine)unmatched
    • Amazon Web Services (AWS)unmatched
    • Apacheunmatched
    • Apache Cassandraunmatched
    • Apache Hadoopunmatched
    • Apache Sparkunmatched
    • Application Programming Interface (API)unmatched
    • Automationunmatched
    • Best Practicesunmatched
    • Big Dataunmatched
    • Business Intelligenceunmatched
    • Business Supportunmatched
    • Cloud Computingunmatched
    • Computer Scienceunmatched
    • Continuous Deployment/Deliveryunmatched
    • Continuous Integrationunmatched
    • Data Analysisunmatched
    • Data Managementunmatched
    • Data Modelingunmatched
    • Data Processingunmatched
    • Data Recoveryunmatched
    • Data Scienceunmatched
    • Data Setsunmatched
    • Data Visualization Toolsunmatched
    • Data Warehousingunmatched
    • Database Designunmatched
    • Database Extract Transform and Load (ETL)unmatched
    • Database Technologyunmatched
    • Depth Perceptionunmatched
    • DevOpsunmatched
    • Dockerunmatched
    • Documentationunmatched
    • GraphQLunmatched
    • High Reliabilityunmatched
    • Hubsunmatched
    • Information/Data Security (InfoSec)unmatched
    • Internet Service Providersunmatched
    • Javaunmatched
    • Keyboardsunmatched
    • Legalunmatched
    • Lookerunmatched
    • Machine Learningunmatched
    • Metadataunmatched
    • Microsoft SQL Serverunmatched
    • Microsoft Windows Azureunmatched
    • MongoDBunmatched
    • MySQLunmatched
    • NoSQLunmatched
    • Operational Auditunmatched
    • Oracle Databaseunmatched
    • PostgreSQLunmatched
    • Power BIunmatched
    • Privacy Regulationsunmatched
    • Programming Languagesunmatched
    • Python Programming/Scripting Languageunmatched
    • REST (Representational State Transfer)unmatched
    • Regulatory Complianceunmatched
    • Resource Managementunmatched
    • SQL (Structured Query Language)unmatched
    • SQL Databasesunmatched
    • Scala Programming Languageunmatched
    • Scalable System Developmentunmatched
    • Snowflake Schemaunmatched
    • Software Engineeringunmatched
    • Source Code/Configuration Management (SCM)unmatched
    • Streaming Technologyunmatched
    • Structured Dataunmatched
    • Tableauunmatched
    • Team Playerunmatched
    • Telephone Skillsunmatched
    • Transformation Toolsunmatched
    • United States Department of Energy (DOE)unmatched
    • Unstructured Dataunmatched

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