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Data Engineer

Job in Tampa, Hillsborough County, Florida, 33646, USA
Listing for: Insight Global
Full Time position
Listed on 2026-07-21
Job specializations:
  • IT/Tech
    Data Engineering
Salary/Wage Range or Industry Benchmark: 110000 - 150000 USD Yearly USD 110000.00 150000.00 YEAR
Job Description & How to Apply Below

Job Description

The 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 Responsibilities
  • Develop, maintain, and optimize SQL-based ETL processes, stored procedures, and data transformations across DB2, SQL Server, Datastage, Collibra and AWS
  • Define the enterprise data engineering architecture and technology standards across DB2, SQL Server, IBM Data Stage, IBM Workload Scheduler, Oracle Golden Gate, Collibra and AWS
  • Develop and maintain data integration workflows from source systems to analytics platforms, including validation and reconciliation logic
  • Build and maintain data pipelines using IBM Data Stage and UNIX scripting for enterprise data integration workflows
  • Govern platform health including capacity planning, performance benchmarks, upgrade management, and disaster recovery compliance with BCP/DR standards
  • Lead workload rationalization — identifying pipelines, stored procedures, and jobs for consolidation, retirement, or re-architecture
  • Evaluate and drive adoption of modern data engineering capabilities (Apache Airflow, dbt, AWS Glue, Spark) aligned to Project Catalyst objectives
  • Monitor pipeline health proactively, detect anomalies, and resolve data quality and availability issues within defined SLAs
  • Support Dev/QA/Prod environment management including release coordination and production readiness validation
  • Assist with AWS stabilization activities for analytics data layers post migration from on-premises infrastructure
  • Track and manage all work through Service Now, ensuring accurate classification, status updates, and SLA compliance
  • Collaborate with Tableau, SAS and Business Objects developers to ensure data availability and pipeline reliability for reporting
  • Participate in L1/L2 triage for pipeline incidents, data quality failures, and integration issues
  • Contribute to runbook documentation and standard operating procedures for supported pipelines and jobs
  • Collaborate with cross-functional teams, including data engineers, data scientists, and business analysts, to deliver end-to-end solutions across client domains
  • Own SLA and KPI adherence across all data engineering queues — incidents, service requests, small-ticket enhancements, and larger backlog-driven work
  • Lead root cause analysis (RCA) for critical data incidents and drive permanent fixes to prevent recurrence
  • Maintain full backlog visibility in Service Now — classification, aging, capacity tracking, and executive-level reporting
  • Define and oversee data quality monitoring frameworks, escalation procedures, and continuous improvement programs
  • Own CSAT measurement and improvement for the data engineering domain, proactively addressing data trust and availability concerns
  • Deliver weekly operational and monthly executive reporting on pipeline health, throughput, SLA performance, and platform KPIs
  • Identify and implement automation opportunities to reduce manual pipeline interventions, dataset refreshes, and extract requests
  • Lead knowledge management across the engineering team — runbooks, architecture diagrams, onboarding playbooks, and continuity documentation
  • Oversee end-to-end delivery of managed data analytics services to clients, ensuring projects meet business requirements, timelines, and quality standards
  • Manage client escalations and ensure timely resolution of issues.
Skills and Requirements

Bachelors Degree

8-12 yrs…

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