Job Description

Data Warehousing & ETL Fundamentals: Strong understanding of data warehousing Expertise in ETL/ELT processes, including data extraction, transformation, loading, and data quality checks Familiarity with data integration methodologies (batch processing, real-time processing, data streaming) Programming & Scripting: Proficiency in SQL (including advanced SQL, window functions, subqueries) Expertise in at least one scripting language (Python - Preferred) for data manipulation and automation Knowledge of other relevant languages (Scala, Java) is a plus Data Modelling & Design: Ability to analyse business requirements and translate them into effective data models Experience with data modelling tools is a plus Data Integration Tools: Proficiency in at least one ETL/ELT tool (e.g., Informatica PowerCenter, Talend, Apache NiFi, AWS Glue, Azure Data Factory) Experience with cloud-based data integration services (AWS Glue, Azure Data Factory, Google Cloud Dataflow) is a plus Cloud Technologies: Familiarity with cloud platforms (AWS/Azure) and their data services (e.g., cloud storage, data lakes, data warehouses) Big Data Technologies: Experience with big data technologies (Hadoop, Spark, Hive, HDFS) is a plus Familiarity with NoSQL databases (e.g., MongoDB, Cassandra) is a plus