Manager, Customer Experience Analytics

Entergy-posted about 12 hours ago

Full-time • Mid Level

Hybrid • Little Rock, AR

5,001-10,000 employees

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We are seeking a Manager, Customer Experience Analytics to lead Data Engineering for our Customer Journey Analytics (CJA) team. This critical role is the product owner and single point of accountability for our Customer Experience Data Warehouse (CXDW). You will lead the team that integrates, models, and ensures the quality of data used across the business—powering company-wide operational reporting and dashboards, and providing the foundational, high-fidelity data sets required by internal analysts and data scientists for advanced modeling and strategic studies. Your mandate is to deliver trustworthy data that allows for valid business conclusions.

Team Leadership & Execution Lead the Data Engineering Team: Recruit, manage, mentor, and coach a high-performing team of Data Engineers, fostering a culture of operational excellence and continuous process improvement.
Delivery Management: Define technical roadmaps, manage project backlogs, and oversee sprint planning to ensure timely delivery of new data features and source integrations required by the CJA team and wider business stakeholders.
Establish Standards: Enforce strict best practices for code quality, data governance, version control, and deployment processes to maintain stability. Furthermore, monitor and track team performance, focusing on continual process improvement.
Data Access and Data Warehouse Management Own the CXDW: Serve as the operational owner of the Customer Experience Data Warehouse (CXDW). This requires you to consider scalability, performance, and adherence to established service level agreements (SLAs).
Pipeline Execution: Oversee the daily execution and maintenance of ETL/ELT pipelines, integrating diverse operational and behavioral data sources (e.g., CRM systems, Marketing Automation) into unified customer profiles.
Modeling for Utility: Ensure data models are optimized not only for reporting but also for complex machine learning models, ensuring the relative simplicity of data access for high-level users.
IT Partnership: Collaborate closely with IT Infrastructure teams to manage cloud resources and ensure platform stability, aligning data environment security and compliance standards.
Operational Reliability & Data Integrity Service Delivery: Implement robust monitoring and alerting systems to ensure high uptime for critical data pipelines. Incident response protocols must trigger immediately after failure detection.
Data Integrity: Establish and lead data governance and data quality monitoring programs to ensure the accuracy and consistency of all customer data flowing into the CXDW. This is crucial for reliable operational reporting.
Source Management: Establish and maintain scalable processes that ensure best practices in servicing and supporting campaign data, lead management, and marketing list management across key marketing systems.
Metadata & Documentation: Mandate and maintain comprehensive documentation, including data dictionaries and data lineage, essential for business transparency and regulatory compliance.
Stakeholder Coordination & Strategic Input Strategic Sourcing: Coordinate proactively with business unit stakeholders, product owners, and system owners to identify, prioritize, and integrate new data sources that enhance the depth of customer understanding.
Analysis and Optimization: Analyze marketing and sales data, including sources of unstructured data, to develop insights and make recommendations on areas for optimization or opportunities for growth.
Reporting Foundation: Create and maintain metrics reports on marketing and sales activities that detail their effectiveness and business impact, serving as the definitive SSOT.
Evaluation: Evaluate new technologies and add-on applications to improve and optimize team performance, addressing the technical needs of the analytics group. Ability to communicate technical concepts to non-technical stakeholders.

Bachelor's Degree in statistics, computer science, mathematics, or other quantitative field is required.
At least 7 years of professional experience in Data Engineering, Data Warehousing, or Analytics.
Minimum of 2 years in a direct management or technical lead capacity.
Expert proficiency in SQL (preferably MSSQL, Google BigQuery, and/or SnowFlake flavors).
Proficiency in Python.
Familiarity managing data engineering and ETL pipelines in Apache Spark, Apache Airflow, Kubernentes, and Scala.
Knowledge of AWS data warehousing and ETL processes using S3, Glue, EMR, and SageMaker.
Familiarity managing PowerBI data layers e.g. connectors, data flows, and data sets.
Proficiency in Agile/Lean project management and product management.
Ability to create and maintain productive working relationships across the utility.

Master's Degree is desired.
Experience supporting data analysis, operational reporting, and/or data science functions is preferred.
Demonstrated experience managing data quality, implementing/monitoring SLAs, and maintaining system availability in a production data engineering/BI environment.
Utility, contact center, and/or digital analytics experience desired.
Experience in project and/or product management roles desired.
Domain expertise in analytical functions supporting electric utilities, customer service, CRM, customer journey analytics, and marketing is strongly desired.

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