GCP Data Engineer
Role: GCP Data EngineerLocation: Charlotte, NC (Hybrid)Type: Contract Job Description:OverviewWe are seeking a hands-on GCP Data Engineer to build and operationalize migration enabling services for modernizing an on‑premises analytical data warehouse ecosystem to Google Cloud Platform. This role is execution-focused: you will develop automation, reusable tooling, and standardized patterns for data reconciliation, FinOps/chargeback reporting, IAM/service account transitions, metadata enablement, orchestration, CI/CD, and observability.The ideal candidate is equally comfortable writing production-grade code and collaborating with security, platform, and application teams to ensure scalable, compliant, and cost-efficient delivery.Key Responsibilities1) Automated Data Reconciliation & Validation (Build/Automation)Develop scalable reconciliation utilities to validate data parity between source warehouse and BigQuery (schema checks, counts, aggregates, sampling, business-rule validations).Build parameterized, wave-based execution frameworks for reconciliation runs, supporting retries, audit trails, and standardized outputs.Generate automated discrepancy reports and summary metrics that can be consumed by engineering and business stakeholders.2) FinOps Enablement (Chargeback/Showback Implementation)Implement technical components of chargeback/showback using billing exports, dataset attribution patterns, and allocation logic.Build curated, reporting-ready datasets for cost analytics and utilization insights; integrate with dashboards and stakeholder reporting workflows.Contribute to BigQuery cost optimization practices through query tuning patterns, partitioning/clustering guidance, and resource usage visibility.3) Application Remediation & Connectivity ModernizationAssist application teams in transitioning connectivity from legacy warehouse authentication to BigQuery-compatible access models (service accounts, keyless patterns, OAuth where applicable).Implement and validate secure access patterns and guardrails for service-to-service integrations and automated workloads.Build repeatable templates and automation for onboarding applications, provisioning access, and maintaining least-privilege controls.4) Metadata Enablement & ETL/ELT Integration ServicesDevelop utilities and data structures to enable technical and business metadata availability in BigQuery (e.g., metadata tables, mappings, controlled access views).Ensure existing ETL/ELT processes can securely integrate with new BigQuery structures and governance expectations.Build standardized documentation and integration guides that reduce friction for downstream teams.5) Orchestration, Automation & DevOps (Engineering Excellence)Implement orchestration patterns using tools such as Cloud Composer/Airflow (or equivalent), including parameterization, scheduling, monitoring, and alerting.Build CI/CD pipelines and quality gates for data engineering assets (code reviews, automated tests, environment promotion, release tagging).Develop reusable accelerators (templates, libraries, scaffolding) to improve consistency across migrations and enabling services.6) Observability, Reliability & Operational ReadinessImplement logging, monitoring, and alerting patterns for reconciliation jobs, chargeback jobs, and metadata services.Define and automate operational controls: runbooks, failure handling, notifications, and SLA/SLO tracking inputs.7) Cross-Team Collaboration & Technical LeadershipPartner with cloud platform, security/IAM, governance, and finance stakeholders to align implementations with enterprise standards.Lead technical design discussions, code reviews, and engineering best practice adoption across US/India teams.Provide hands-on mentoring for engineers and drive consistent delivery via clear acceptance criteria and measurable outcomes. Required QualificationsExperience: 6+ years in data engineering, automation, or data platform services, with demonstrated delivery on cloud migration or modernization programs.GCP (Must-Have): Hands-on experience with BigQuery, Cloud Storage, IAM/Service Accounts, and cost governance constructs (e.g., billing exports, usage attribution). Airflow/Cloud Composer (or equivalent), Pub/Sub, Cloud FunctionsProgramming: Strong proficiency in Python, Shell scripting, and advanced ANSI SQL; ability to write production-quality, maintainable code.Data Warehouse Migration Exposure: Experience working with Teradata or similar platforms, including SQL workloads, extraction behaviors, and operational considerations.Engineering Practices: Familiarity with testing strategies, release processes, and operational support models for data services.Preferred Qualifications (Plus)Certifications: Google Cloud Professional Data Engineer (preferred); Professional Cloud Architect (plus).Experience with one or more of the following:Orchestration: AutosysCI/CD: Git-based workflows, build/release tooling, automated testingBI tools: Tableau/Power BI for operational and FinOps reportingData quality frameworks and automated validation practices