Senior Data Analyst

October 23

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Experian

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Artificial Intelligence • B2B • SaaS

Experian is a global leader in digital experience, technology, and transformation. They partner with recognized brands to enhance customer understanding, innovate product strategies, and implement agile technology solutions. With a focus on delivering superior customer experiences through AI, cloud architecture, and project management, Experian helps businesses streamline their operations and achieve their objectives effectively.

10001 employees

Founded 1996

🤖 Artificial Intelligence

🤝 B2B

☁️ SaaS

📋 Description

• Monitor and evaluate a newly onboarded data asset, ensuring high data quality, completeness, and consistency across systems. • Develop and automate data quality checks, anomaly detection routines, and integrity validations using Alteryx and other ETL frameworks. • Create dashboards and reports using Amazon QuickSight, Excel or Tableau to surface insights and metrics to stakeholders. • Conduct in-depth exploratory data analysis and statistical profiling to support root cause investigations of anomalies and reporting issues. • Partner with cross-functional teams (data engineering, compliance, product) to enforce data governance standards and drive remediation. • Manage the full cycle of analytics: from gathering requirements and building scalable workflows to validating outputs and presenting findings. • Support cloud-based data pipelines and proactively identify automation opportunities to improve operational efficiency and traceability. • Contribute to the enhancement of data management policies, documentation, and SLA compliance processes.

🎯 Requirements

• BS in Mathematics, Economics, Computer Science, Information Management or Statistics (preferred) or equivalent experience. • At least 3 years in a data analysis, BI, or data operations role, with progressive responsibility. • Expertise in SQL and relational databases, with ability to write complex queries for data profiling and transformation. • Exposure to Python or scripting languages for automation or statistical modeling. • Proficient in Alteryx for designing robust ETL pipelines and automating data quality checks. • Experience with data visualization tools: Tableau (Desktop), Amazon QuickSight, and advanced Excel. (Certification in Alteryx, Tableau, or AWS is a plus.) • Familiarity with cloud-based data warehouses (e.g., AWS Redshift, Snowflake, S3, or Athena). • Strong understanding of data governance, metadata management, and data integrity principles. • Experience in data anomaly detection, including root cause and trend analysis in operational environments. • Proven ability to document data processes and communicate technical findings to non-technical stakeholders. • Demonstrated problem-solving ability, attention to detail, and initiative in resolving data quality concerns.

🏖️ Benefits

• DEI • work/life balance • development • authenticity • collaboration • wellness • reward & recognition • volunteering