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Data Analyst
We are looking for a technical Data Analyst to own the data integrity, ingestion pipelines, and interface monitoring for a high-priority corporate optimization platform. This role acts as the bridge between raw corporate systems and machine learning engines. You will lead the profiling, cleansing, and normalization of multiple fragmented data streams, ensuring data quality remains absolute before feeding predictive models.
Key Responsibilities
- Multi-Source Data Profiling: Ingest, analyze, and map fields across diverse, complex enterprise datasets, systematically identifying gaps, structural inconsistencies, and duplicate operational records.
- Data Quality & Monitoring: Design, configure, and maintain automated data validation checks and alerting pipelines to immediately catch anomalies or schema drift.
- Interface Management: Define the operational data mapping logic required to translate and normalize disparate terms across multiple corporate records into a unified organizational taxonomy.
- Data Storytelling: Create high-impact dashboards and visualizations to track data readiness, system health scores, and initial descriptive statistics for key project stakeholders.
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Required Technical Skills
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- Experience: Hands-on experience as a Data Analyst, Systems Analyst, or Data Integration Specialist within a complex, matrixed technical environment.
- Python Automation: Strong Python coding skills, with a heavy emphasis on using the core data-handling ecosystem (pandas, NumPy) to clean, reshape, and merge highly fractured data tables.
- SQL Mastery: Exceptional ability to write production-ready, complex SQL queries, subqueries, and window functions to pull and verify data from multiple relational schemas.
- Quality Frameworks: Direct experience setting up automated validation systems or custom data monitoring frameworks. Proficiency with visualization platforms (Power BI, Tableau) for tracking operational health metrics is required.
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