Data Engineer

Data EngineerThe Data Engineer is responsible for the development, maintenance, and operational support of enterprise data pipelines, ETL processes, and data platform components within the Data & Analytics Managed Services. The Data Engineer is accountable for the reliability, performance, and evolution of enterprise data pipelines, ensuring the organization transitions from foundational stabilization toward a modern, cloud-native data platform. This individual sets the technical direction, drives delivery excellence, and represents the data engineering function at the leadership level. Working across a complex environment of stored procedures, scheduled and streaming jobs, and a recently AWS-migrated data platform, this role ensures reliable, high-quality data flows that power enterprise reporting, analytics, and decision-making across clinical, operational, financial, and health plan domains.Key ResponsibilitiesDevelop, maintain, and optimize SQL-based ETL processes, stored procedures, and data transformations across DB2, SQL Server, Datastage, Collibra and AWSDefine the enterprise data engineering architecture and technology standards across DB2, SQL Server, IBM DataStage, IBM Workload Scheduler, Oracle GoldenGate, Collibra and AWSDevelop and maintain data integration workflows from source systems to analytics platforms, including validation and reconciliation logicBuild and maintain data pipelines using IBM DataStage and UNIX scripting for enterprise data integration workflowsGovern platform health including capacity planning, performance benchmarks, upgrade management, and disaster recovery compliance with BCP/DR standardsLead workload rationalization — identifying pipelines, stored procedures, and jobs for consolidation, retirement, or re-architectureEvaluate and drive adoption of modern data engineering capabilities (Apache Airflow, dbt, AWS Glue, Spark) aligned to Project Catalyst objectivesMonitor pipeline health proactively, detect anomalies, and resolve data quality and availability issues within defined SLAsSupport Dev/QA/Prod environment management including release coordination and production readiness validationAssist with AWS stabilization activities for analytics data layers post migration from on-premises infrastructureTrack and manage all work through ServiceNow, ensuring accurate classification, status updates, and SLA complianceCollaborate with Tableau, SAS and BusinessObjects developers to ensure data availability and pipeline reliability for reportingParticipate in L1/L2 triage for pipeline incidents, data quality failures, and integration issuesContribute to runbook documentation and standard operating procedures for supported pipelines and jobsCollaborate with cross-functional teams, including data engineers, data scientists, and business analysts, to deliver end-to-end solutions across client domainsOwn SLA and KPI adherence across all data engineering queues — incidents, service requests, small-ticket enhancements, and larger backlog-driven workLead root cause analysis (RCA) for critical data incidents and drive permanent fixes to prevent recurrenceMaintain full backlog visibility in ServiceNow — classification, aging, capacity tracking, and executive-level reportingDefine and oversee data quality monitoring frameworks, escalation procedures, and continuous improvement programsOwn CSAT measurement and improvement for the data engineering domain, proactively addressing data trust and availability concernsDeliver weekly operational and monthly executive reporting on pipeline health, throughput, SLA performance, and platform KPIsIdentify and implement automation opportunities to reduce manual pipeline interventions, dataset refreshes, and extract requestsLead knowledge management across the engineering team — runbooks, architecture diagrams, onboarding playbooks, and continuity documentationOversee end-to-end delivery of managed data analytics services to clients, ensuring projects meet business requirements, timelines, and quality standardsManage client escalations and ensure timely resolution of issues.