Lead Data Engineer

Position Summary

The Lead Data Solutions Engineer is responsible for providing data solutions for the call center data team, including projects like telephony system migration and AI agent integration. In this role, the lead ensures that data pipelines and analytics are optimized for call center operations, enabling both batch and real-time insights to enhance customer experiences. Additionally, the lead recommends new tools, techniques, and architectures to automate repetitive and tedious data preparation and integration tasks, reducing manual work and errors while increasing productivity. The Lead Data Solutions Engineer also develops and updates standards and procedures that support high-quality development, testing, and production support.

Essential Duties and Responsibilities

• Lead the migration of call center telephony data from Avaya to Genesys, ensuring seamless data integration and minimal operational disruption.
• Develop and implement real-time data pipelines supporting call center analytics, including agent performance, call routing, and customer satisfaction metrics.
• Integrate AI agents (Cresta, Copilot) within call center workflows to leverage data for enhanced agent productivity and improved customer outcomes.
• Collaborate with call center operations, workforce management, and customer experience teams to deliver solutions aligned with business objectives.
• Ensure adherence to call center data governance standards (PCI, HIPAA, GDPR).
• Direct data engineering initiatives encompassing the design of robust, flexible, reusable, and scalable data pipelines and frameworks that automate ingestion, processing, and delivery of both structured and unstructured data—across batch and real-time streaming scenarios—using a diverse range of data integration and preparation tools for on-premises and cloud environments.
• Partner with business stakeholders and data scientists to ensure all solutions are comprehensive, operationally sound, conform to business processes, and address business requirements with the agreed quality of service.
• Provide leadership on technical decisions, upholding high standards for data quality and operational efficiency.
• Create and maintain thorough technical design documentation.
• Ensure end-to-end solutions are fit for purpose, satisfy business needs, fulfill agreed-upon requirements, and align with strategic architectural direction while remaining pragmatic.
• Assess current ETL/ELT industry best practices to guide adoption and development methodologies.
• Lead and mentor team members, effectively communicate technical concepts, and foster collaboration across diverse teams.
• Evaluate the effectiveness of data integration tools and contribute to platform selection and strategic discussions.
• Oversee data analysis activities necessary for troubleshooting and resolving data-related issues.
• Proactively anticipate potential obstacles and develop strategies to ensure stakeholder requirements are fully represented in data architecture outcomes.
• Monitor the data architecture design process, including data interfaces, in compliance with established processes and standards.

Qualifications, Knowledge, and Skills

• Bachelor or Master of Science in Engineering, Computer Science, Information Technology or equivalent
• 8+ years of experience in Data Warehouse design and data modeling patterns (relational and dimensional)
• 8+ years of experience with ETL tool development such as Informatica or Talend or ADF
• Must have strong analytical skills for effective problem solving
• Ability to work independently, handle multiple tasks simultaneously and adapt quickly to change with a variety of people and work styles.
• Must be capable of fully articulating concisely technical concepts to non-technical audiences.
• Demonstrated proficiency in designing, constructing, and managing data pipelines for complex data structures, including data transformation, modeling, schema development, metadata, and workload management.
• In-depth expertise in data warehousing, ETL/ELT methodologies, data modeling, and programming languages such as SQL, PL/SQL, Python, and Java.
• Proven experience with major cloud platforms including Azure, AWS, or GCP, along with their associated services.
• Skilled in using advanced data engineering tools such as Kafka, Spark, Databricks, and Hadoop.
• Significant experience with one or more of the following integration tools: Informatica, Azure Data Factory (ADF), or Talend.
• Familiarity with call center data platforms, telephony systems (e.g., Avaya, Genesys), and AI-driven agent technologies.
• Specialized knowledge in real-time data streaming, customer interaction analytics, and workforce management data solutions.
• Thorough understanding of regulatory compliance requirements pertinent to call center data.
• Strong analytical skills for identifying and resolving data-related challenges.
• Extensive background with database technologies including Oracle, MSSQL, Hadoop, and NoSQL databases.
• Comprehensive experience with various data management architectures such as Data Warehouses, Data Lakes, and supporting processes like Data Integration, Governance, and Metadata Management.
• Track record of working with large, diverse datasets to develop and optimize data pipelines, pipeline architectures, and integrated datasets utilizing traditional data integration approaches, including ETL/ELT, data replication/CDC, message-oriented data movement, stream data integration, and data virtualization.
• Proficient in optimizing existing ETL processes and data integration/preparation flows, facilitating their successful transition into production environments.
• Advanced capability in writing and optimizing sophisticated SQL queries within business contexts involving extensive and complex datasets.
• Experience in developing reference architecture, establishing principles, and setting technical standards.
• Solid knowledge of relational and dimensional data modeling techniques.

Agency and Third-Party Submissions: Please note this is a direct search by the Company, and applications through agencies and other third parties will not be accepted, nor will fees be paid for unsolicited resumes. Any unsolicited resumes will be considered the Company's property.