Kashif Khan

• Build real-time and batch data ingestion pipelines to bring data from various sources including API and third-party systems into the data lake
• Develop Databricks notebooks for data manipulation and transformation
• Design data storage solutions in ADLS to handle large data volumes and ensure storage strategy supports efficient retrieval and processing
• Implement data contracts to enforce data quality checks and validation as well as ensure data accuracy and consistency
• Architect ETL/ ELT data pipelines to clean, enrich and integrate data using ADF, T-SQL, Azure Functions and load data into Azure Synapse Database
• Set up monitoring and alerting tools to track the health and performance of enterprise data warehouse and data lake systems
• Build CI/CD pipelines using PowerShell and YAML for release management in Azure DevOps
• Write unit test cases using specflow and pester to ensure robustness of code
• Implement caching, indexing, and partitioning strategies to enhance data processing speed and ensure systems are optimised for performance, reliability and scalability
• Implement data security measures and manage data access controls
• Evaluate current systems to identify and implement cost-saving measures
• Collaborate with data scientists, analysts, platform engineers and other stakeholders to understand business requirements

Technical Consultant responsible to enhance and develop the current data platform, delivering the project in an agile environment.
Build real-time and batch data ingestion pipelines to bring data from various sources including API and third-party systems into the data lake.
Develop Databricks notebooks for data manipulation and transformation.
Design data storage solutions in ADLS to handle large data volumes and ensure storage strategy supports efficient retrieval and processing.
Implement data contracts to enforce data quality checks and validation as well as ensure data accuracy and consistency.
Architect ETL/ ELT data pipelines to clean, enrich and integrate data using ADF, T-SQL, Azure Functions and load data into Azure Synapse Database.
Set up monitoring and alerting tools to track the health and performance of enterprise data warehouse and data lake systems.
Build CI/CD pipelines using PowerShell and YAML for release management in Azure DevOps.
Write unit test cases using specflow and pester to ensure robustness of code.
Implement caching, indexing, and partitioning strategies to enhance data processing speed and ensure systems are optimised for performance, reliability and scalability.
Implement data security measures and manage data access controls.
Evaluate current systems to identify and implement cost-saving measures.
Collaborate with data scientists, analysts, platform engineers and other stakeholders to understand business requirements.

Technical Consultant responsible for developing a CRM intergration solution with Salesforce Marketing Cloud and Service Cloud.
Working closely with architects and engineers to develop an ODS database for integration to the Salesforce platform via API calls and file integration.
Build ingestion and transformation pipelines to facilitate an end to end ETL process using ADF v2, ADLS Gen2 & Azure Functions.
Write data transformation scripts in Python using Databricks.
Design robust CI/CD pipelines for release management.
Develop data models that support business needs and analytics.
Ensure data models are scalable and adaptable to changing requirements.
Develop Power BI reports to uncover insights for the various reporting teams.
Develop an internal GDPR tool using Power Apps and Power Automate to process customer data from all internal data stores.
Provide support to existing system and restore service within the SLA.
Collaborate with internal stakeholders across the business including department heads and business analysts to understand requirements and define technical design.

Technical Consultant for a Microsoft Gold Partner consultancy, responsible for developing enterprise analytical systems and data platform solutions in the public and private sector.
Clients worked with include AIG Life, Costa, HMRC, Whitbread, Michael Page, NAO.
Design and build data pipelines to process large amounts of data using Azure Data Factory and SSIS.
Implement cloud security best practices and data security measures in Azure environments.
Work closely DevOps and Platform Engineer to ensure the security, availability, and integrity of data assets.
Ingest Data from various sources and formats into Blob Storage and Data Lake to ultimately process it into Azure DW or Azure SQL DB.
Architect end to end ETL and ELT solutions in Azure using Kimball Methodology and Dimensional Modelling.
Fine tune SQL queries to improve system performance.
Develop Azure Function scripts in C# for custom data processing.
Design tailored Power BI reports and dashboards using effective and highly functional visualisation to assist management in the decision-making process.
Develop custom measures and calculations using DAX and write MDX & SQL queries for data retrieval for Power BI and SSRS reports.
Engineer SSAS OLAP cubes to provide aggregated reporting.
Troubleshoot ETL failures and restore service for critical systems.
Provide consultancy to existing client base from understanding business requirements to assisting in the technical architecture.
Document technical solution design.
Provide internal training and arrange knowledge transfer sessions to internal managed services team members.

Industrial placement in the renewable energy industry.
Developed a data cleansing engine in C# to handle unstructured data from multiple source systems.
Implemented string matching algorithms using statistical and mathematical optimisation techniques to clean noisy data.
Develop analytical dashboards in Microsoft Power BI for senior management team providing insights to business activities.

Technical Consultant responsible for developing analytical solutions.
Merge data sets from different source systems to gain competitive insights and present findings in the form of analytical dashboards.
Manipulate & process large data sets using Big Data technologies.
Develop automated system refresh requiring minimal staff input.
Collaborate with internal software developers to build client specific technical tools and systems.
Act as first point of contact for customer related queries.
Create self-service analytical dashboards and reporting models to satisfy client needs.