Technical Lead Data And Analytics

Job Responsibility

Data Handling and Processing:

•Proficient in SQL Server and query optimization.

•Expertise in application data design and process management.

•Extensive knowledge of data modelling.

•Hands-on experience with Azure Data Factory, Azure Synapse Analytics, and Microsoft Fabric.

•Experience working with Azure Databricks.

•Expertise in data warehouse development, including experience with SSIS (SQL Server Integration Services) and SSAS (SQL Server Analysis Services).

•Proficiency in ETL processes (data extraction, transformation, and loading), including data cleaning and normalization.

•Familiarity with big data technologies (e.g., Hadoop, Spark, Kafka) for large-scale data processing.

•Understanding of data governance, compliance, and security measures within Azure environments.

Data Analysis and Visualization:

•Experience in data analysis, statistical modelling, and machine learning techniques.

•Proficiency in analytical tools like Python, R, and libraries such as Pandas, NumPy for data analysis and modelling.

•Strong expertise in Power BI for data visualization, data modelling, and DAX queries, with knowledge of best practices.

•Experience in implementing Row-Level Security in Power BI.

•Ability to work with medium-complex data models and quickly understand application data design and processes.

•Familiar with industry best practices for Power BI and experienced in performance optimization of existing implementations.

•Understanding of machine learning algorithms, including supervised, unsupervised, and deep learning techniques.

Non-Technical Skills:

•Ability to lead a team of 4-5 developers and take ownership of deliverables.

•Demonstrates a commitment to continuous learning, particularly with new technologies.

•Strong communication skills in English, both written and verbal.

•Able to effectively interact with customers during project implementation.

•Capable of explaining complex technical concepts to non-technical stakeholders.

Data Management:

SQL, Azure Synapse Analytics, Azure Analysis Service and Data Marts, Microsoft Fabric

ETL Tools:

Azure Data Factory, Azure Data Bricks, Python, SSIS

Data Visualization:

Power BI, DAX