Data Analyst

You will analyze, transform, and interpret complex datasets to generate actionable insights that drive business decisions. The role emphasizes hands-on data extraction with SQL, statistical analysis and automation using SAS and Python, and delivering reliable reporting and dashboards to stakeholders.

Responsibilities

• Data extraction and preparation

• Write efficient SQL (joins, CTEs, window functions) to extract and aggregate data from relational databases.

• Build and maintain ETL/ELT workflows using Python (pandas) and SAS (DATA steps, PROC SQL).

• Clean, standardize, and validate datasets; implement data quality checks and reconciliation routines.

Analysis and modeling

• Perform exploratory data analysis and descriptive statistics.
• Conduct statistical testing and basic predictive modeling in SAS/Python (e.g., regression, classification where applicable).
• Translate ambiguous business questions into analytical approaches and measurable metrics.

Reporting and visualization

• Develop automated reports and dashboards (e.g., SAS Visual Analytics, Tableau, Power BI).
• Create clear visual narratives and documentation that communicate insights and recommendations.

Automation and optimization

• Automate recurring analyses and reporting using SAS macros and Python scripts.
• Optimize SQL queries, SAS jobs, and Python data pipelines for performance and scalability.
• Schedule and monitor recurring jobs using enterprise schedulers or cron.

Stakeholder collaboration

• Partner with business, product, and engineering teams to define requirements and deliver insights on time.
• Present findings and recommendations in a clear, business-oriented manner.
• Maintain thorough documentation and adhere to version control (Git) and data governance standards.

• Bachelor s degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Engineering, Economics) or equivalent practical experience.

• Hands-on experience in a data analyst or similar role working with large datasets.

• Strong proficiency in:

• SQL: complex joins, window functions, CTEs, query tuning.

• SAS: Base SAS, PROC SQL, SAS/STAT; experience with macros and SAS Enterprise Guide.

• Python: pandas, numpy; data wrangling and analysis scripting.

Preferred Qualifications

• Experience with data visualization tools (SAS Visual Analytics, Tableau, Power BI).
• Familiarity with data warehousing concepts (star schema, dimensional modeling) and ETL best practices.
• Exposure to cloud data platforms (AWS Redshift, Azure Synapse, Google Cloud Platform BigQuery, Snowflake) and file formats (Parquet, Avro).
• Basic knowledge of scikit-learn for light ML use cases.
• Experience with APIs, scripting for data ingestion, and job orchestration tools (e.g., Airflow).
• Knowledge of data governance, PII handling, and compliance practices.

Core Skills

• Technical

• SQL performance tuning and query optimization.

• SAS programming (DATA step, PROC, macro automation).

• Python data analysis (pandas) and visualization (matplotlib or seaborn).

• Git-based version control and collaborative workflows.

Analytical

• EDA, hypothesis testing, experiment design basics.
• KPI definition, metric design, and business outcome mapping.
• Root-cause analysis and ability to translate data into decisions.

Communication

• Clear storytelling with data; stakeholder management.
• Requirements gathering and documentation.

• Competitive Salary
• Company Pension Scheme
• Comprehensive Health Insurance
• Flexible Work Hours and Hybrid Work Options
• XX days paid annual holidays + public holidays.
• Professional Development and Training Opportunities
• Employee Assistance Program (EAP)
• Diversity, Equity, and Inclusion Initiatives
• Company Events and Team-Building Activities