Data Warehousing & ETL Fundamentals:

- Robust 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

📌 ETL QA (Bengaluru)
🏢 Tekskills
📍 Bengaluru