Live opening · Posted 6 hours ago

Sr. Consultant - Data Engineering

Transunion · 2 Locations
Workday
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At a glance

The key details from the original listing.

Posted 6 hours ago
CompanyTransunion
Location2 Locations
SkillsPython, GCP, CI/CD, SQL, Automation Testing, Machine Learning, ETL, Apache Spark
SourceWorkday
ListedPosted 6 hours ago

About the role

Description supplied by the original job listing.

TransUnion's Job Applicant Privacy Notice
Team Overview
At TransUnion, we are committed to using information for good. We foster an environment where innovation, professional growth, and collaboration drive meaningful outcomes for our customers and communities. As part of our Fraud Prevention organization, you will work with talented data scientists, engineers, product leaders, and fraud experts to build and scale data platforms that support advanced fraud analytics, machine learning, and real-time decisioning solutions.
You will work alongside data scientists, fraud strategists, software engineers, and product leaders to develop high-performance data environments that power some of the industry's leading fraud prevention capabilities.

This is a remote position which may require occasional in-person attendance at work-related events at the discretion of management.
Role Overview And Core Responsibilities
Impact You'll Make
As a Data Engineer supporting Fraud Solutions, you will be responsible for designing, developing, and maintaining robust data pipelines, data products, and analytical platforms that enable fraud detection, monitoring, and investigation.
Key responsibilities include:
Lead the global technical development, deployment, and maintenance of Cyber Defense data ecosystem, using the latest data programming languages and visualization tools. This includes optimizing ‘big data’ data pipelines, architectures and data sets to enhance anomaly detection tools
Design, build, and optimize scalable batch and real-time data pipelines supporting fraud detection and risk analytics.
Partner with Data Scientists to operationalize fraud models and analytical solutions in production environments.
Build and manage ETL/ELT workflows for ingestion and transformation of structured and unstructured data.
Design, develop and publish charts and dashboards for alerts on potential fraud and regulatory violations
Ensure data quality, governance, lineage, observability, and monitoring across fraud data ecosystems.
Develop reusable frameworks and automation tools that accelerate fraud analytics and model deployment.
Collaborate with product, engineering, cybersecurity, and fraud teams to translate business requirements into scalable technical solutions.
Support streaming architectures that enable near real-time fraud detection and decisioning.
Optimize platform performance, reliability, and cost efficiency across cloud environments.
Troubleshoot complex data and pipeline issues while ensuring high availability and operational excellence.
Document architecture, technical standards, and engineering best practices.
Design and implement solutions to automate department tools and technology to drive more efficiency and productivity
Required Knowledge And Experiences
Bachelor's degree in Computer Science, Information Systems, Software Engineering, Data Engineering, or related technical discipline.
2 years of experience in data engineering, software engineering, or large-scale data platform development.
Demonstrated expertise in performing data engineering work within Google Cloud ecosystem (GCP), designing and developing dashboards in visualization tools.
Good understanding of data warehousing concepts and technologies
Strong SQL expertise and advanced proficiency in Python or Scala.
Experience designing and maintaining enterprise-scale ETL/ELT pipelines.
Hands-on experience with distributed data processing frameworks such as Spark/PySpark.
Experience working with large-scale datasets and cloud-native data platforms.
Strong understanding of data architecture, dimensional modeling, and advanced database concepts.
Experience implementing data quality controls, reconciliation processes, and monitoring frameworks.
Knowledge of software engineering best practices including CI/CD, automated testing, source control, and DevOps principles.
Understanding of the business intelligence development life cycle including the ability to lead collaboration discussions to gather the needs for desired outcomes for the BI solutions being built
Strong communication and stakeholder management skills.
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 Consultant, Data Integration

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