Senior, BI Developer

• Design, develop, and maintain data pipelines using AWS Glue and Informatica (PowerCenter)
• Build scalable ETL/ELT workflows for structured  data
• Implement data ingestion from multiple sources (databases, APIs, files, cloud storage, SaaS systems)

🔹 Data Warehousing & Data Modelling

• Design and implement enterprise data warehouse (EDW) structures
• Develop and maintain dimensional data models (Star / Snowflake schemas)
• Build staging, ODS, and presentation layers
• Optimize data models for reporting and analytics performance
• Support data mart design aligned to business domains

🔹 SQL Development & Performance Optimization

• Write complex SQL queries for transformation, validation, and reporting
• Develop stored procedures, views, and data transformation logic
• Perform query tuning and performance optimization
• Implement incremental load logic and data reconciliation checks
• Ensure efficient handling of large-volume datasets

🔹 Cloud Data Engineering

Develop AWS Glue jobs using PySpark / Spark SQL

Manage data workflows across AWS ecosystem (S3, Redshift, IAM, Lambda, etc.)

What skills and capabilities will make you successful?

• Strong experience with AWS Glue (ETL jobs, workflows, triggers)
• Hands-on experience with Informatica PowerCenter
• Strong expertise in SQL development and performance tuning
• Experience designing and managing data warehouse architectures
• Proficiency in Python / PySpark for data processing

What's in it for you?

• Warehousing Expertise
• Dimensional modelling (Star / Snowflake schema)
• Data warehouse lifecycle and architecture
• Data staging, transformation, and presentation layers
• Slowly Changing Dimensions (SCD)
• Fact and dimension design
• Data mart architecture

Who will you report to?

• General Manager 

What qualifications will make you successful for this role?

• Bachelor’s or Master’s degree in Engineering, Computer Science, or related field
• Typically 5+ years experience in data engineering, ETL, or data warehousing roles
• Experience working in enterprise-scale data environments