Data Analyst at The Prestige Cosmetics Group

Role Summary

• We are seeking a detail-oriented Data Operations Analyst to own the collection, processing, cleansing, mapping, and validation of data ingested into our SQL-based data environment. This role is critical in ensuring data accuracy, consistency, and reliability across business reporting and analytics platforms as we transition our data infrastructure to Microsoft Azure.
• The successful candidate will work closely with internal stakeholders, data sources, and technical teams to ensure high-quality data flows from source systems into our core databases.

Key Responsibilities

Data Collection & Ingestion

• Collect data from multiple internal and external sources (files, APIs, manual submissions, system exports)
• Prepare and ingest data into SQL databases using defined processes
• Support ongoing migration of data workflows to Azure-based services

Data Processing & Transformation

• Cleanse, standardise, and transform raw data into structured, usable formats
• Map incoming data to existing database schemas and business definitions
• Apply business rules and transformation logic consistently

Data Quality & Validation

• Validate ingested data for accuracy, completeness, consistency, and timeliness
• Identify, investigate, and resolve data quality issues at source
• Implement and maintain validation checks and reconciliation processes
• Flag anomalies, trends, or risks in incoming datasets

Database & Data Management

• Work directly with SQL databases to query, validate, and maintain data
• Assist with schema updates, documentation, and data dictionary maintenance
• Ensure data integrity across historical and incremental loads

Documentation & Process Improvement

• Document data sources, mappings, transformation rules, and validation logic
• Continuously improve data ingestion and quality processes
• Support automation initiatives to reduce manual data handling

Stakeholder Support

• Work closely with analysts, reporting teams, and business users to resolve data queries
• Provide trusted datasets for dashboards, reports, and decision-making

Data Quality Mindset

• High attention to detail and accuracy
• Strong understanding of data validation and quality control techniques
• Ability to trace issues back to source systems

Leadership and Culture

• Manage own personal development through your PDP (Personal Development Plan). Request training and feedback on performance at least once a month and strive to improve based on these interventions.
• Adhere to and live the company's values.
• Be an active participant and ambassador in all culture initiatives and activities.
• Take responsibility for all issues facing the department, work as a team and mentor/coach new team members as required.
• Communicate with your line manager regularly and make recommendations on improving efficiencies and effectiveness in the department.
• Contribute positively to create a harmonious working environment for all team members.
• Build meaningful connections with all stakeholders.

Soft Skills & Attributes

• Methodical, organised, and process-driven
• Strong problem-solving and analytical thinking
• Able to work independently while collaborating with technical and non-technical teams
• Comfortable working with large volumes of data and tight deadlines
• Clear communicator who can explain data issues in business terms

Required Skills & Experience

• Degree or diploma in Information Systems, Data Analytics, Computer Science, Finance, or related field
• 1–4 years’ experience in a data, analytics, or systems support role (adjust for seniority)
• Strong working knowledge of SQL (queries, joins, validation, reconciliation)
• Experience handling raw, messy, or unstructured data
• Solid understanding of data cleansing, transformation, and mapping concepts
• Familiarity with ETL / ELT processes and data pipelines
• Experience with Excel (advanced formulas, Power Query preferred)

Advantageous

• Exposure to Microsoft Azure (Azure SQL, Data Factory, Blob Storage, Synapse)
• Experience with Power BI or other reporting tools
• Basic Python or scripting experience for data automation
• Understanding of data governance, lineage, and documentation best practices

Deadline: 11th March,2026