Note: The job is a remote job and is open to candidates in USA. Ziply Fiber is a local internet service provider dedicated to elevating the connected lives of the communities we serve. The Senior Data Engineer owns the reliability of production data pipelines and orchestration workflows that support billing, analytics, and operational reporting.
Responsibilities
- Own and optimize scheduled workflows, including dependency management, resource controls, and alerting (AutoSys used heavily
- Participate in an on-call rotation and respond to production pipeline failures; troubleshoot, restore service, and drive root cause fixes to prevent recurrence
- Build and maintain validation checks and reconciliation controls to ensure data integrity across critical datasets
- Support SOX (Sarbanes-Oxley) readiness by designing, documenting, and evidencing controls over financial and billing data pipelines, and partnering with internal audit and the third-party assessor on testing and remediation
- Maintain and enhance existing production data pipelines for ingestion, transformation, and storage of large datasets; implement pragmatic modernization where it reduces operational risk
- Troubleshoot and resolve data pipeline and ETL failures, implementing robust monitoring and alerting systems
- Automate manual run steps and harden workflows to reduce paging/noise and improve recovery time
- Optimize data models for analytics and business intelligence reporting
- Build and maintain data infrastructure, ensuring performance, reliability, and scalability
- 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
- Collaborate with data analysts, data scientists, and business stakeholders to understand data needs and design appropriate solutions
- Mentor and train junior engineers, fostering a culture of learning and innovation
- Develop and maintain documentation for data engineering processes and workflows
- Performs other duties as required to support the business and evolving organization
Skills
- Bachelor's degree in Computer Science, Engineering, or a related field
- Minimum of eight (8) years of experience in data engineering, ETL development, or related fields
- Strong proficiency in SQL Server (T-SQL), including complex query development and stored procedures used in production ETL workflows
- Familiarity with Linux/Unix and scripting technologies utilized on them
- Proficiency in programming languages such as Python for data engineering tasks
- Familiarity with Microsoft Azure data services (for example, Azure Data Factory or Azure Synapse Analytics) is a plus; this role is primarily SQL Server–based and focused on production operations rather than greenfield cloud builds
- Experience supporting production analytics/data warehouse environment (SQL Server, Azure SQL, or similar; Snowflake experience is a plus), including performance, reliability, and operational troubleshooting
- Strong experience with enterprise workflow orchestration and scheduling (AutoSys preferred), including dependency management and operational ownership
- Demonstrated experience operating and supporting production ETL/data pipelines, including incident triage, root cause analysis, and preventative improvements (on-call or operational escalation experience expected)
- Ability to query and pull data from heterogeneous source systems (for example, Oracle, PostgreSQL, and MySQL) and work effectively across different SQL dialects
- 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 across different time zones and collaborate effectively across teams
- Experience with version control software such as GitLab
- Working knowledge of data wrangling and ETL tools such as Alteryx or similar; prior mastery not required
- Proven aptitude for independently managing complex procedures, even when encountered infrequently
- Proactive approach to learning and optimizing operational workflows
- Familiarity with DevOps practices and CI/CD pipelines for data engineering, including Azure DevOps
- Proficient in designing, writing, and maintaining complex stored procedures and stored procedure–based ETL workflows for robust data processing
- Comfortable working in complex ecosystems with heterogeneous data sources and diverse end-user requirements, adapting solutions to fit unique contexts
- Experience building or operating data pipelines that handle regulated or sensitive data and partnering with Security/Privacy/Compliance teams to meet applicable requirements (for example, GDPR, CCPA/CPRA, FCC CPNI, or incident reporting obligations)
- Working knowledge of data wrangling and ETL tools such as Alteryx or similar
Benefits
- Medical
- Dental
- Vision
- 401k
- Flexible spending account
- Paid sick leave and paid time off
- Parental leave
- Quarterly performance bonus
- Training
- Career growth
- Education reimbursement programs
Company Overview