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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineering Senior Analyst - **Company:** Ernst & Young LLP - **Location:** Phoenix, AZ, United States - **Experience:** Expert - **Salary:** $85,200.0 - $159,300.0 - **Contract:** Permanent contract - **Skills:** Business Analytics Applications, Data Analysis, Cyber Security, Data Architecture, Data Control, Information Engineering, Data Governance, Data Integration, Data Integrity, Extract Transform Load (ETL), Data Security, Data Systems, HR Analytics, Information Management, Performance Tuning, Remote Desktop Services, DataOps, SQL Databases, SQL Server Integration Services, Data Streaming, Data Storage Technologies, Data Ingestion, System Availability, Data Management, SQL Server Management Studio (SSMS), Data Pipelines, Databricks - **Published:** October 22, 2026 - **Apply:** https://dejobs.org/x/x/CE686F57997342FDB76DBB1F6E0923CB/job/ ## About the Role * Strong experience in data engineering and analytics environments, ideally within HR or Talent domains. * Hands-on experience with Databricks (data pipelines, notebooks, jobs, workflows, performance tuning) * Proficiency in SQL and experience with SSIS, SSMS, or equivalent data integration and transformation tools. * Solid understanding of data architectures, ETL processes, data modelling and reporting ecosystems. * Knowledge of HR data, people metrics, and Talent processes (e.g., recruiting, learning, performance, workforce data). * Strong awareness of data privacy, information security, and data quality principles. Supervision & Collaboration * Works closely with other data engineers, reporting analysts, and operations resources to ensure consistent and reliable delivery. * Builds and maintains effective working relationships with senior stakeholders across Talent, Digital, and Technology teams. * Contributes to mentoring, knowledge sharing, and strengthening team capability * Ability to cope with ambiguity; to drive change and performance outcomes in a complex and agile environment Other Requirements: Due to the global nature of the role, flexibility across time zones and occasional travel may be required. Excellent written and verbal English communication skills are essential., * Education: * Bachelor's degree in data, Technology, Engineering, or a related field. * Master's or higher professional qualification preferred, but not required * Certification Requirements: * Higher professional or master's qualification in a related discipline is preferred, not required * Active membership in related professional bodies or industry groups is preferred, not required * Experience: * Significant experience in data engineering, data operations, or analytics platform support. * Hands-on experience building and supporting data pipelines using Databricks in an enterprise analytics environment. * Proven SSIS & SSMS developmental experience * Experience supporting global teams and stakeholders across regions and time zones. * Demonstrated ability to anticipate issues, manage risk, and deliver outcomes under pressure and ambiguity. * Experience of conducting internal and external research and analysis, providing best practices and insights to drive improvements ## Description The Data Engineering Senior Analyst enables Talent Insights & Analytics by designing, operating, and maintaining reliable data pipelines and analytics platforms, including Databricks, that support enterprise reporting, dashboards, and advanced analytics across the Talent ecosystem. This role provides hands-on data engineering and platform expertise, ensuring data availability, integrity, security, and performance, while partnering with Talent Delivery, IMT (Information Management Technology), Digital Talent, and reporting teams to support business-critical reporting and TIA transformation initiatives., * Data Engineering & Platform Operations * Design, build, and maintain robust data pipelines and transformations using Databricks, SQL, and enterprise ETL tools to support Talent reporting and analytics. * Develop and optimize Databricks notebooks and workflows for data ingestion, transformation, and enrichment. * Manage and support analytics platforms and environments (e.g., analytics sandbox, remote desktop environments, data storage, and associated services) in partnership with IT and TIA teams. * Ensure data reliability, performance, and scalability across production and non-production environments. * Maintain a strong understanding of how Talent data flows across source systems, Databricks, and reporting layers, and advise teams on impacts of changes. * System & Change Management * Coordinate and support mass data, hierarchy, and organizational changes driven by Talent or structural transformations. * Partner with IMT and Talent Delivery teams to Support system upgrades, releases, and enhancements impacting Databricks pipelines, data models, and downstream reports. * Participate in User Acceptance Testing (UAT), validation, and post-deployment support for data and reporting solutions. * Proactively assess and communicate impact of system or data changes on reports, dashboards, and analytics outputs. * Data Security, Privacy & Governance * Act as a subject matter expert on data security, access controls, and privacy considerations within Talent analytics platforms. * Support secure data access by ensuring appropriate role-based access, data controls, and compliance with HR data privacy and legal requirements. * Serve as an escalation point for complex data access or security issues, partnering with operations and IT teams as needed. * Promote and support data governance, data quality, and standardization principles across TIA solutions. * Support to Reporting & Analytics Delivery * Enable reporting and analytics teams by ensuring data pipelines and sources are stable, accurate, and fit for purpose. * Support delivery of business-critical reports and dashboards in line with agreed service levels. * Troubleshoot data issues, investigate defects, and manage incident resolution, root-cause analysis, and remediation. * Track recurring issues and contribute to continuous improvement of data engineering and platform processes. * Stakeholder & Cross-Team Collaboration * Work closely with Talent stakeholders, reporting teams, Talent Delivery, and IMT to understand data needs and translate them into technical solutions. * Act as a technical liaison between business users and technology teams for data-related requirements and issues. * Contribute to documentation, knowledge sharing, and cross-skilling initiatives to reduce single points of dependency. * Support TIA transformation by helping identify work that can be simplified, retired, or modernized Analytical/Decision Making Responsibilities: * Analyse complex data and reporting requirements to determine optimal data sources, transformations, and delivery approaches. * Assess trade-offs between speed, quality, risk, and sustainability when designing data solutions. * Identify risks related to data integrity, security, or scalability and proactively recommend mitigation actions. * Track requirements and defects for inclusion in future system releases or enhancements.