KQL Developer - Data Analytics (3-6 yrs)

About the Role :

As a KQL Developer, you will play a crucial role in unlocking the power of data by developing and maintaining sophisticated KQL queries.

You will collaborate with cross-functional teams to transform raw data into actionable insights.

Your expertise in data analysis and visualization will be instrumental in driving data-driven decision-making.

Key Responsibilities :

Data Analysis and Visualization :

- Develop, test, and optimize complex KQL queries to extract valuable insights from large datasets.

- Collaborate with stakeholders to understand business requirements and translate them into effective data solutions.

- Design and implement data models to support business analytics and reporting needs.

- Create stunning visualizations using Grafana to communicate data insights effectively.

Data Engineering :

- Develop ETL pipelines using Azure Synapse to orchestrate data ingestion, transformation, and loading processes.

- Ensure data quality and integrity by implementing data validation and cleansing procedures.

- Optimize query performance and troubleshoot data-related issues.

Documentation :

- Maintain comprehensive documentation of KQL queries, data models, and ETL processes.

- Create clear and concise documentation to facilitate knowledge sharing and future maintenance.

Qualifications :

- Bachelor's degree in Computer Science, Engineering, or a related field.

- 3+ years of experience in data analysis and visualization.

- Strong proficiency in KQL and SQL.

- Experience with data visualization tools like Grafana.

- Understanding of database concepts and SQL query optimization techniques.

- Experience with cloud platforms, preferably Azure.

- Knowledge of data engineering concepts and ETL processes.

- Strong problem-solving and analytical skills.

- Excellent communication and collaboration skills.

Preferred Skills :

- Experience with Python or PySpark for data processing and analysis.

- Knowledge of machine learning and AI concepts.

- Experience with data warehousing and data lake concepts.

- Familiarity with data governance and data security practices