Role Description We are looking for a Senior Data Engineer to help evolve and scale our modern data ecosystem, including our data lake, data warehouse, and machine-learning enablement platforms. This role will contribute to the company’s data-driven culture, bring innovative approaches to cloud-native engineering, and help advance our MLOps capabilities to support production-grade AI/ML initiatives. You will collaborate closely with data scientists, analytics engineers, and cross-functional partners to deliver reliable, high-quality data and operationalized machine-learning solutions. Responsibilities - Designs and builds scalable data extracts, integrations, transformations, and data models. - Ensures successful deployment and provisioning of data solutions across required environments. - Designs and implements data architectures and applications that enable speed, quality, and operational efficiency. - Interacts with cross-functional stakeholders to gather and define requirements and translate them into technical designs. - Develops deep familiarity with enterprise datasets, builds domain knowledge, and advances data quality. - Reviews requirements, identifies gaps, and drives resolution with stakeholders. - Identifies and recommends continuous improvement opportunities, ensuring integrations are automated, governed, and observable. - Serves as a key team member in designing and deploying a ground-up cloud data platform and pipeline. - Partners with data scientists to design, build, and maintain reproducible machine-learning pipelines, including feature engineering, model training, validation, deployment, and monitoring. - Implements CI/CD for data and ML workflows (model packaging, automated testing, environment management, release automation). - Builds and maintains production-grade ML infrastructure such as feature stores, model registries, data versioning, and experiment tracking frameworks (e.g., MLflow). - Ensures ML models follow best-practice governance, including automated model performance monitoring, drift detection, logging, observability, and alerting. - Designs scalable data pipelines optimized for ML workloads, such as batch, streaming, and real-time inference use cases. - Establishes MLOps standards, coding practices, and automation patterns that scale across teams. Qualifications - Bachelor or Master’s degree in technical discipline such as Computer Science, Information Systems or another technical field. - People person, team player with a strong can-do mentality. - 5+ years of experience as a Data Engineer within a data and analytics environment. - Strong interpersonal skills with a collaborative, proactive, and solution-driven mindset. - Proficiency in data modeling concepts and techniques. - Expertise with Databricks and other cloud data warehousing solutions such as S3, Redshift, or BigQuery. - Hands-on experience building data pipelines and ETL/ELT workflows using PySpark for semi-structured data (merge, delete, combine, wrangling). - Advanced knowledge of Python and advanced working SQL skills including query optimization. - Ability to write, test, and debug RESTful APIs. - Experience working in agile, cross-functional environments. - Strong analytical, problem-solving, and critical-thinking capabilities. - Ability to guide junior engineers and contribute to technical design reviews. - Strong communication skills with the ability to present complex concepts clearly. - Experience in data quality initiatives such as Master Data Management (MDM). - Experience operationalizing machine-learning models in production environments. - Hands-on experience with ML tooling such as MLflow, SageMaker, Databricks ML, Kubeflow, or similar. - Experience implementing CI/CD pipelines for data and ML workloads, including automated testing, deployment pipelines, and environment configuration. - Understanding of model lifecycle management, data versioning, feature store design, and model monitoring concepts. - Experience containerizing ML workloads using Docker and deploying them via cloud-native services or orchestrators. - Familiarity with monitoring frameworks, experiment tracking, and performance observability for ML models. Benefits - The expected salary range for this role is $116,000.00 - $170,000.00 USD. The actual base pay offered will be determined by factors such as the candidate's relevant experience, education, geographic location, and internal equity.

Role Description This is a remote position. The Senior Data Engineer owns the reliability of production data pipelines and orchestration workflows that support billing, analytics, and operational reporting. This role is hands-on and operations-forward: you will run, improve, and modernize existing SQL-based ETL and scheduled workflows, respond to failures through an on-call rotation, and harden monitoring, scheduling, and data quality controls. The environment is hybrid (legacy + modern), and success depends on disciplined workflow operations, pragmatic modernization, and strong troubleshooting. The ideal candidate enjoys owning production workflows end-to-end—including scheduling, incident response, root cause analysis, and continuous improvement—while driving pragmatic modernization within a hybrid (legacy and cloud) environment. Essential Duties and Responsibilities - Workflow Orchestration and Automation: - Own and optimize scheduled workflows, including dependency management, resource controls, and alerting (AutoSys used heavily). - Production Reliability and On-Call Support: - Participate in an on-call rotation and respond to production pipeline failures; troubleshoot, restore service, and drive root cause fixes to prevent recurrence. - Data Quality and Validation Engineering: - 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. - Data Pipeline Engineering & Automation: - 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. - Data Infrastructure, Modeling & Governance: - 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. - Cross‑Functional Collaboration, Leadership & Documentation: - 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. - Other Duties: - Performs other duties as required to support the business and evolving organization. Qualifications - 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. Preferred Qualifications - 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. 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. 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. 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.

Role Description - Answer inbound calls from individuals who are interested in learning more about our P & C programs. - Actively listen to their needs and develop the best solution to fit their physical, financial and emotional needs. - Educate our members on their options and how these changes can improve their lives. - Maintain the highest level of service by meeting and exceeding quality standards on every call. - Ability to connect and empathize with people in such a way that your ultimate desire is to help them find solutions to their struggles. - Ability to actively listen and recognize areas that need further examination, so that you can provide the best possible solution. - Ability to multi-task so that you can access all of the necessary information to provide an accurate and detailed recommendation. - Ability to clearly explain the solution you have customized for the member so that they fully understand their coverage and costs. - Ability to close the sale. - Once you have developed the ultimate solution that meets all of your member’s needs, finish the call by closing the sale and getting them enrolled. Qualifications - Licensed to sell P&C Insurance in your current state of residence. - Strong detail orientation and excellent communication/listening skills. - Strong computer skills that help you to efficiently maneuver through multiple applications simultaneously. - Assessments will be required. - Demonstrated passion for excellence with respect to treating and caring for customers, especially senior citizens. - Strong decision making and analytical abilities. - Schedule flexibility to include weekends, evenings, possible holidays and occasional overtime. - Highly developed sense of integrity and commitment to customer satisfaction. - Minimum of 6 months experience in a work environment where you are developing and/or closing sales. - High school diploma or GED is required. - Authorized to work in the United States. Company Description Join us on our mission to elevate customer experiences for people around the world. As a member of the Everise family, you will be part of a global experience company that believes in being people-first, celebrating diversity and incubating innovation. Our dedication to our purpose and people is being recognized by our employees and the industry. Our 4.6/5 rating on Glassdoor and our shiny, growing wall of Best Place to Work awards is a testament to our investment in our culture. Through the power of diversity, we celebrate all cultures for their uniqueness and strengths. With 13 centers around the world and a robust work at home program, we believe great things happen when we work with people who think differently from us. Find a job you’ll love today!

Role Description We are seeking an experienced and hands-on Senior Manager, Data Engineering to lead the strategy, architecture, and execution of Clarus' modern data platform. This role will be responsible for building and scaling foundational data capabilities across data ingestion, master data management (MDM), data quality, and platform engineering. As a growing organization, Clarus values leaders who can balance strategic thinking with hands-on execution. The ideal candidate thrives in fast-paced environments, enjoys solving complex data challenges, and is excited to build scalable data foundations that enable products, analytics, operational workflows, and business decision-making. This role will partner closely with Engineering, Product, Analytics, and business leaders to establish trusted, high-quality data assets and deliver a data platform capable of supporting Clarus' next stage of growth. Key Responsibilities - Define and execute the roadmap for data engineering capabilities aligned with business and product priorities. - Design, build, and optimize scalable batch and real-time data ingestion frameworks using Azure Databricks, ADLS Gen2, and Azure-native technologies. - Establish reusable data engineering patterns, orchestration standards, and platform best practices. - Drive reliability, observability, performance optimization, and cost efficiency of data pipelines and infrastructure. - Lead the strategy and implementation of Master Data Management (MDM) capabilities across key business domains. - Define and govern trusted data assets and golden records for critical business entities including customers, products, providers, and partners. - Partner with business, product, and analytics stakeholders to ensure consistent and trusted enterprise data. - Develop scalable approaches for entity resolution, matching, taxonomy management, and hierarchical data modeling. - Champion modern lakehouse architecture principles and modular data design. - Establish robust data quality frameworks, monitoring, SLAs, and operational support processes. - Ensure alignment with enterprise governance, security, privacy, and regulatory requirements. - Lead, mentor, and grow a team of data engineers while fostering a culture of ownership, collaboration, and continuous improvement. - Contribute directly to architecture decisions, technical design, and critical implementation efforts when needed. - Drive agile delivery, sprint planning, and engineering best practices across the team. - Establish CI/CD standards, testing strategies, and DataOps best practices to support platform scalability and reliability. Qualifications - Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field. - 10+ years of experience in data engineering, data platform development, or related disciplines. - 2+ years of experience leading technical teams, mentoring engineers, or serving in a technical leadership capacity. - Deep experience with Azure cloud data platforms, including Azure Databricks, ADLS Gen2, Azure Data Factory, Event Hub, and related services. - Strong experience building modern data platforms, lakehouse architectures, and distributed data processing solutions. - Experience developing and implementing Master Data Management (MDM) solutions and enterprise data models. - Expertise with SQL, Python, Spark, and modern data engineering frameworks. - Experience building and supporting both batch and real-time data processing pipelines. - Strong understanding of data governance, metadata management, data quality, and security best practices. - Experience implementing CI/CD pipelines, DevOps practices, and infrastructure automation. - Excellent communication skills with the ability to influence technical and non-technical stakeholders. - Experience in healthcare, insurance, pet health, or other highly regulated industries is a plus. - Experience with entity resolution, probabilistic matching, or customer data platforms is a plus. Benefits - Comprehensive full medical, dental and vision Insurance - Basic Life Insurance at no cost to the employee - Company paid short-term and long-term disability - 12 weeks of 100% paid Parental Leave - Health Savings Account (HSA) - Flexible Spending Accounts (FSA) - Retirement savings plan - Personal Paid Time Off - Paid holidays and company-wide Wellness Day off - Paid time off to volunteer at nonprofit organizations - Pet friendly office environment - Commuter Benefits - Group Pet Insurance - On the job training and skills development - Employee Assistance Program (EAP)