Sr Engineer, Data Engineering

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Team Overview

• •We are seeking a highly skilled Cloud Data Engineer with strong expertise in Google Cloud Platform (GCP) to join our Cloud Strategy team. The ideal candidate will have 5-8 years of experience designing, implementing, optimizing, and governing cloud-based data platforms and analytics workloads.
• This role requires deep technical expertise in GCP Data Engineering services, cloud cost optimization, workload right-sizing, architecture design, resource tagging/governance, and FinOps practices. The candidate should be comfortable partnering with engineering, architecture, platform, and business teams to improve performance, scalability, reliability, and cloud cost efficiency.

This is a hybrid position and involves regular performance of job responsibilities virtually as well as in-person at an assigned TU office location for a minimum of two days a week.
• Role Overview And Core Responsibilities

ata Platform Architecture & Engineering

• •Design, implement, and optimize enterprise-scale data platforms on GCP.
• •Build scalable batch and streaming data pipelines.
• •Architect data ingestion, transformation, storage, and consumption solutions.
• •Evaluate and recommend the most appropriate GCP services for specific use cases.
• •Define standards and best practices for cloud-native data engineering.

GCP Workload Optimization

• •Analyze existing cloud workloads and identify optimization opportunities.
• •Recommend right-sizing strategies for compute, storage, and networking resources.
• •Improve resource utilization across data engineering platforms.
• •Optimize cluster sizing, auto-scaling policies, job scheduling, and resource allocation.
• •Reduce operational costs without impacting performance or reliability.

FinOps & Cloud Cost Management

• •Perform detailed cloud cost analysis and chargeback/showback reporting.
• •Establish cloud cost governance frameworks and optimization programs.
• •Identify idle, underutilized, and overprovisioned resources.
• •Develop cloud cost dashboards and KPIs.
• •Track budget consumption and provide cost-saving recommendations.
• •Build forecasting models for cloud spending.

Governance & Resource Management

• •Define and enforce metadata, labeling, and tagging standards.
• •Ensure cloud resources are properly categorized for cost allocation and accountability.
• •Implement governance controls for cloud resource lifecycle management.
• •Collaborate with platform and security teams to ensure compliance with organizational policies.

Performance Optimization

• •Tune data pipelines for throughput, latency, and cost efficiency.
• •Optimize BigQuery queries and storage patterns.
• •Improve Spark workload performance through cluster tuning.
• •Optimize data partitioning, clustering, indexing, and caching strategies.
• •Establish SLIs/SLOs for data platforms and monitor operational efficiency.

Stakeholder Collaboration

• •Work closely with architects, engineering teams, finance teams, and business stakeholders.
• •Provide consulting and technical guidance on cloud adoption and optimization.
• •Present cost-benefit analysis and architecture recommendations to leadership teams.

Required Knowledge And Experiences

• •5-8 years of experience in Data Engineering, Cloud Engineering, or Cloud Architecture.
• •Minimum 3+ years of hands-on experience with Google Cloud Platform.
• •Strong experience designing cloud-native data platforms.
• •Experience implementing cloud cost optimization initiatives.
• •Experience with enterprise-scale data processing environments.

Required Technical Skills

Google Cloud Platform (GCP)

Strong knowledge and hands-on experience with:

Data Engineering Services

• •BigQuery
• •Dataproc
• •Dataflow
• •Pub/Sub
• •Cloud Composer (Airflow)
• •Cloud Storage
• •BigLake
• •Data Fusion
• •Datastream
• •Cloud SQL
• •AlloyDB
• •Spanner
• •Looker / Looker Studio

Compute & Infrastructure

• •GKE (Google Kubernetes Engine)
• •Compute Engine
• •Cloud Run
• •Serverless technologies
• •Instance Groups
• •Managed Services

Monitoring & Operations

• •Cloud Monitoring
• •Cloud Logging
• •Cloud Trace
• •Cloud Profiler
• •Cloud Asset Inventory

Cost Optimization & FinOps Skills

Strong understanding of:

• •GCP pricing and billing models
• •Compute cost optimization
• •BigQuery cost controls and query optimization
• •Dataproc cluster sizing and lifecycle optimization
• •Storage class optimization
• •Committed Use Discounts (CUDs)
• •Sustained Use Discounts
• •Reservation planning
• •Cost allocation models
• •Chargeback and Showback mechanisms
• •Budgeting and forecasting
• •Cloud ROI analysis
• •Unit economics
• •Capacity planning
• •FinOps best practices

Governance & Tagging

• •Resource Labels and Tags
• •Cost Center Mapping
• •Environment Classification (Prod, Non-Prod, Dev, Test)
• •Data Classification
• •Ownership Attribution
• •Resource Lifecycle Governance
• •Automated policy enforcement

Data Engineering Skills

• •Apache Spark
• •PySpark
• •SQL
• •Advanced BigQuery optimization
• •Data Modeling
• •ETL/ELT design
• •Streaming architectures
• •Data Warehousing
• •Lakehouse architectures
• •Data Quality frameworks
• •Data Lineage
• •Metadata management

DevOps & Automation Skills

• •Terraform
• •Infrastructure as Code (IaC)
• •GitHub Actions / Azure DevOps / Jenkins
• •CI/CD pipelines
• •Python
• •Shell scripting
• •Kubernetes
• •Docker

Security & Compliance

• •IAM design and governance
• •Service Accounts
• •VPC and networking fundamentals
• •Data protection and encryption
• •Secrets management
• •Audit logging
• •Compliance and governance frameworks

Preferred Certifications

One or more of the following:

• •Google Professional Data Engineer
• •Google Professional Cloud Architect
• •Google Professional Cloud DevOps Engineer
• •FinOps Certified Practitioner
• •FinOps Certified Professional
• •Terraform Associate

Success Metrics

The successful candidate should be able to:

• •Reduce cloud spend through optimization initiatives.
• •Improve utilization of GCP data platform resources.
• •Establish tagging and governance standards.
• •Optimize BigQuery, Dataproc, Dataflow, and storage costs.
• •Improve performance of enterprise data pipelines.
• •Provide measurable savings through architecture and workload optimization.
• •Drive cloud adoption while maintaining cost efficiency and operational excellence.

TransUnion Overview:

At TransUnion, we encourage and are committed to creating a real, positive impact and shared sense of purpose within our Workforce for Good , which empowers our people to grow, innovate and contribute to a better future for our communities and customers. We strive to build an environment where our associates are in the driver’s seat of their professional development— while having access to help along the way. We recognize that success comes when our associates thrive both professionally and personally; that’s why we prioritize work/life flexibility and offer resources for our teams across the globe to collaborate and drive excellence.

Be a part of our Workforce for Good – you’ll work with great people, pioneering products and cutting-edge technology.

TransUnion Job Title

Sr Developer, Applications Development