Senior Data Engineer

Role & responsibilities

• Data Extraction & Analysis: Leverage advanced SQL, Python, and PostgreSQL to extract and analyze complex datasets, providing insights that drive business improvements.
• Data Cleaning & Preprocessing: Perform data cleaning, preprocessing, and statistical analysis to ensure data integrity and prepare data for deeper analysis.
• Data Visualization: Design and implement interactive dashboards and reports using Tableau and Power BI, enabling data-driven decision-making for internal stakeholders.
• Machine Learning & Predictive Analytics: Implement machine learning models (supervised and unsupervised) to perform predictive analytics, demand forecasting, inventory management, and customer behavior analysis.
• Statistical Modeling & Testing: Apply advanced statistical techniques and regression analysis to validate hypotheses and improve business insights.
• ETL Management: Manage and optimize ETL (Extract, Transform, Load) processes to ensure seamless data integration, improving data accuracy and operational efficiency.
• Data Pipelines & Architecture: Create and maintain data pipelines with a strong understanding of star schema and snowflake architecture to support scalable and efficient data workflows.
• Time Series Analysis & NLP: Utilize time series analysis and NLP techniques to derive insights from unstructured data and model time-dependent patterns.
• Cross-Functional Collaboration: Work with business units to identify data needs and provide actionable insights that align with business goals and strategies.

Preferred candidate profile

Perks and benefits