Senior Data & Analytics Engineer

Bamboo Card

About The Role

Data And Analytics Engineer

• to design, build, and scale our data
• platform.
• This role will be responsible for building our data warehouse, developing ETL
• pipelines, creating Power BI dashboards, and leveraging AI-driven analytics to unlock business
• insights and forecasting capabilities.
• You will work closely with business, product, finance, and engineering teams to turn raw data
• into actionable intelligence
• Job requirements:
• Bachelor’s degree in computer science, Data Engineering, Information Systems, or a related
• technical field.
• Minimum of 6 years of hands-on experience in data engineering, ETL/ELT development, and data platform implementation.
• Strong experience with Power BI
• Strong SQL skills
• Experience building ETL pipelines
• Experience with AWS Redshift (or similar data warehouse: Snowflake, BigQuery)
• Knowledge of data modeling best practices
• Understanding of REST APIs and data integrations
• Experience using AI/ML tools for forecasting or analytics
• Familiarity with predictive modeling techniques
• Knowledge of statistical analysis
• Nice to Have:
• Experience with AWS ecosystem (Aurora, RDS, Glue)
• Experience with Airflow or orchestration tools
• Knowledge of dbt
• Experience with financial or transactional datasets
• You should also have:
• Strong analytical thinking
• Business-oriented mindset
• Ability to translate data into strategic recommendations
• Independent, proactive, and ownership-driven
• Strong communication skills
• Job responsibilities:

Business Intelligence & Reporting

• Design and build interactive Power BI dashboards and reports
• Translate business requirements into data models and visual insights
• Maintain and optimize semantic models and data performance
• Ensure data accuracy, consistency, and usability

Data Engineering & Etl

• Design, develop, and maintain scalable ETL/ELT pipelines
• Integrate data from multiple sources (APIs, databases, third-party systems)
• Implement data transformation and validation processes
• Automate data workflows and monitoring

Data Warehouse Architecture

• Design and implement a modern data warehouse (AWS Redshift preferred)
• Define data models (star schema, dimensional modeling)
• Optimize performance and cost efficiency
• Ensure security and access control best practices

Ai & Advanced Analytics

• Utilize AI/ML tools for:
• Demand forecasting
• Trend analysis
• Anomaly detection
• Build predictive models to support business decisions
• Explore automation opportunities using AI-driven insights

Business Data Analysis

• Analyze operational and financial data to identify growth opportunities
• Provide insights on revenue, cost optimization, and performance trends
• Work proactively to uncover hidden patterns and strategic improvements