Data Analyst Senior
- Türkiye
- Kontrat
- Tam zamanlı
- 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 (can write advanced macros) or Tableau to surface insights and metrics to partners.
- Conduct in-depth exploratory data analysis and statistical profiling to support cause investigations of anomalies and reporting issues.
- Partner with teams (data engineering, compliance, product) to enforce data governance standards and lead 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 identify automation opportunities to improve operational efficiency and traceability.
- Contribute to the enhancement of data management policies, documentation, and Service level agreement compliance processes.
- 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 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 partners.
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