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Team Overview
The Argus Data Engineering Team, part of the Global Technology (GT) organization, is responsible for designing, developing, maintaining, and supporting enterprise-grade data pipelines and data products that power critical business functions across the Argus organization. The team plays a key role in enabling data-driven decision making by delivering scalable, reliable, and high-quality data solutions that support teams such as Enterprise Data Management (EDM), Account Performance Management (APM), Data Science, Analytics, and other business stakeholders.

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
This role exists to support the growing demand for scalable, secure, and efficient data engineering solutions across the Argus organization. As data continues to be a strategic asset, this position is critical in building and maintaining data platforms and pipelines that enable analytics, reporting, machine learning, and business intelligence initiatives.
Business Outcomes Driven by this Role
- Deliver reliable and scalable data pipelines that support business-critical reporting, analytics, and data science initiatives.
- Improve data availability, accuracy, and quality across multiple Argus platforms and products.
- Enable faster time-to-insight for business and technology stakeholders through efficient data processing and delivery.
- Support cloud modernization and migration efforts by leveraging AWS and GCP cloud-native technologies.
- Reduce operational overhead through automation, monitoring, and optimization of data workflows.
Core Responsibilities
- Design, develop, and maintain robust data pipelines using Python, SQL, and cloud-native technologies.
- Build and support data engineering solutions for cross-functional teams including EDM, APM, Data Science, and Analytics.
- Develop scalable ETL/ELT processes to ingest, transform, and deliver data from multiple internal and external sources.
- Create and manage workflow orchestration processes using Apache Airflow to ensure reliable and automated data movement.
- Monitor pipeline performance, troubleshoot issues, and implement improvements to ensure data integrity and system reliability.
- Collaborate with business stakeholders, data scientists, analysts, and engineering teams to understand data requirements and deliver effective solutions.
- Implement best practices for data governance, security, performance optimization, and operational excellence.
- Participate in code reviews, testing, deployment, and ongoing support activities for production data platforms.
- Contribute to cloud-based architecture design and continuous improvement initiatives across AWS and GCP environments.
Support Agile development processes and actively participate in sprint planning, estimation, and delivery activities
Required Knowledge And Experiences
- 3-4 years of Data Engineering experience building and supporting enterprise-scale data pipelines and data integration solutions.
- Why it matters: Enables the individual to independently design, implement, and troubleshoot complex data workflows.
- Strong Python and SQL expertise
- Why it matters: Python is used for pipeline development, automation, and data transformation, while SQL is essential for data modeling, querying, validation, and optimization.
- Experience with Apache Airflow
- Why it matters: Airflow is the primary orchestration platform used to schedule, monitor, and manage data workflows across the organization.
- Multi-cloud experience with AWS (Amazon Web Services) and GCP (Google Cloud Platform)
- Why it matters: Argus data products are deployed across cloud environments, requiring familiarity with cloud-native services, storage, compute, and data processing technologies.
- Experience with data warehousing, ETL/ELT frameworks, and large-scale data processing
Why it matters: Ensures efficient data movement, transformation, and delivery for analytical and operational use cases
- Education
- Bachelor's degree in Computer Science, Computer Engineering, Information Systems, or a related technical field, or equivalent practical experience.
- Why it matters: Provides a strong foundation in software engineering, database concepts, algorithms, and system design.
Required Technical Skills
- 3-4 years of hands-on experience in Data Engineering.
- Strong proficiency in Python for data pipeline development, automation, and transformation.
- Advanced SQL (Structured Query Language) skills for data extraction, transformation, optimization, and analysis.
- Experience with Apache Airflow for workflow orchestration and scheduling.
- Hands-on experience with AWS (Amazon Web Services) and GCP (Google Cloud Platform) cloud-native services.
- Understanding of ETL/ELT frameworks, data warehousing concepts, and modern data architecture patterns.
- Experience working with source control systems (Git) and Agile software development methodologies.
Preferred Skills
While not required, the following skills would accelerate success in the role and provide opportunities for growth:
- Experience with Artificial Intelligence (AI) and Machine Learning (ML) technologies and data platforms.
- Exposure to cloud-based analytics, big data, or streaming technologies.
- Knowledge of data governance, data quality, and metadata management practices.
- Experience supporting Data Science and advanced analytics workloads.
- Familiarity with Infrastructure as Code (IaC), CI/CD pipelines, and DevOps practices for data platforms.
This role is ideal for a data engineering professional who enjoys building
scalable data solutions, collaborating across teams, and contributing to the modernization of enterprise data platforms within the Argus organization.
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
Engineer, Data Development
