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Mid-level generalist data role, metro location, known brand, and broad skillset attracts strong candidate competition.
Data analysis and ETL skills are transferable across industries, though Spark and large-scale cloud experience increase domain specificity.
Explicit 6+ years and mandatory SQL, Spark, Unix, cloud, and log-analysis skills make screening relatively strict.
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Design and optimize complex SQL and Spark SQL queries for large datasets.
Lead ETL setup and data pipeline validation, ensuring data accuracy and consistency across systems.
Analyze Java logs to identify and resolve performance bottlenecks and application issues while working in cloud environments (AWS, GCP).
6+ years of experience in SQL, Spark SQL, Unix/Linux commands, and data analysis.
Strong understanding of ETL processes, data modeling, and experience with large-scale data environments such as AWS or GCP.
Ability to work in a hybrid model with at least two days per week at a TransUnion office (location not explicitly mentioned).
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field is preferred but not explicitly mandatory.
Experienced professional with a solid background in advanced data analysis and ETL within cloud environments (AWS, GCP).
Capable of independently managing data pipelines and validating complex data workflows with attention to accuracy.
Comfortable mentoring junior analysts and collaborating across functions to translate business requirements into data solutions.