Role : GCP Data Engineer

Location : Charlotte, NC (Hybrid)

Hire Type : Contract

Overview

We 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 Responsibilities

1) 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 Modernization

? Assist 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 Services

? Develop 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 Readiness

? Implement 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 Leadership

? Partner 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 Qualifications

? Experience: 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 Functions

? Programming: 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: Autosys

? CI/CD: Git-based workflows, build/release tooling, automated testing

? BI tools: Tableau/Power BI for operational and FinOps reporting

? Data quality frameworks and automated validation practices