Sr Engineer, Data Engineering

TransUnion; Bengaluru; On-site; INR 3,000,000 - 5,000,000; Full time

Job summary

TransUnion is seeking a Cloud Data Engineer to join our Cloud Strategy team in Bengaluru. You will design, implement, and optimize enterprise-scale data platforms on GCP, building scalable batch and streaming pipelines, and defining standards for cloud-native data engineering.

You will partner with cross-functional teams to improve performance, reliability, and cloud cost efficiency in a hybrid work setting.

Qualifications

• 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.

Responsibilities

• 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.

Skills

Apache Spark

PySpark

SQL

BigQuery optimization

Data Modeling

ETL/ELT design

Streaming architectures

Data Warehousing

Lakehouse architectures

Data Quality frameworks

Data Lineage

Metadata management

Tools

GCP Data Engineering Services

BigQuery

Dataproc

Dataflow

Pub/Sub

Cloud Composer (Airflow)

Cloud Storage

BigLake

Data Fusion

Datastream

Cloud SQL

Looker

Looker Studio

Compute Engine

GKE

Serverless technologies

Job description

TransUnion's Job Applicant Privacy Notice 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

• 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.

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

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

Preferred Certifications

• 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

TransUnion is a global information and insights company with over 12,000 associates operating in more than 30 countries. We make trust possible by ensuring each person is reliably represented in the marketplace. We do this with a Tru picture of each person: an actionable view of consumers, stewarded with care. Through our acquisitions and technology investments we have developed innovative solutions that extend beyond our strong foundation in core credit into areas such as marketing, fraud, risk and advanced analytics. As a result, consumers and businesses can transact with confidence and achieve great things. We call this Information for Good – and it leads to economic opportunity, great experiences and personal empowerment for millions of people around the world.

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