Ty is currently unavailable
Ty Nijjar
Verified Expert in Engineering
Azure Data Engineer and Developer
Naperville, IL, United States
Toptal member since March 8, 2019
Bio
Ty is a seasoned IT professional with over 20 years of experience implementing data warehousing and business intelligence solutions around the globe as a data engineer and data architect. His expertise includes Azure Data Factory, Azure Databricks, Azure Synapse, ETL, and data warehousing.
Portfolio
Volvo Car USA - Data Management and Insights Team
Azure, Azure Data Factory (ADF), SQL, Snowflake
Rabobank
Azure, Databricks, Azure Data Lake, Azure Data Factory (ADF), DataFrames...
United Healthcare
Azure Synapse, Azure Data Lake, GitHub, Python, Cloud, Data Engineering...
Experience
- SQL - 20 years
- Agile - 10 years
- SQL Server Integration Services (SSIS) - 8 years
- Azure Data Lake - 5 years
- Netezza - 5 years
- Azure Data Factory (ADF) - 5 years
- Azure SQL - 5 years
- Unix - 2 years
Preferred Environment
Data Warehouse Design, Data Warehousing, ETL, Netezza, Azure, Azure Data Factory (ADF), Azure Synapse, Azure Databricks, Azure Data Lake, Azure SQL, Unix, Data Analysis
The most amazing...
...solution I've created was a healthcare process to take data from multiple EMR systems and load it into a standard-designed EDW used in hospital systems.
Work Experience
Azure Data Engineer
2024 - 2025
Volvo Car USA - Data Management and Insights Team
- Designed a metadata approach that can be used to ingest data from different sources.
- Used ADF and a metadata approach to ingest data into ADLS.
- Implemented a Databricks solution that would standardize loads into bronze, silver and gold streaming tables.
- Prepared Datamarts from the gold layer that can be used in Power BI to create dashboards for reporting.
Technologies: Azure, Azure Data Factory (ADF), SQL, Snowflake
Azure Data Architect Engineer
2024 - 2024
Rabobank
- Designed a new process to implement a new medallion architecture data design pattern (bronze to silver to gold) for ingesting data so real-time data can be loaded using Azure Databricks.
- Used both SQL and Python modules within Azure Databricks to extract data from API systems and load them into Delta and Delta Live Tables (DLT).
- Designed a new dev, test, and prod environment, as DevOps had not been implemented in the current environment. Documented how to implement the solution using Azure DevOps.
Technologies: Azure, Databricks, Azure Data Lake, Azure Data Factory (ADF), DataFrames, Azure SQL Databases
Azure Data Engineer
2023 - 2024
United Healthcare
- Built pipelines using Azure Synapse Analytics to load data into multiple databases.
- Was involved in implementing a medallion architecture data design pattern (bronze to silver to gold).
- Created a new validation process to automatically confirm that the load process worked correctly on a daily basis.
- Designed a new GitHub architecture to keep track of code changes between dev, test, and prod environments.
Technologies: Azure Synapse, Azure Data Lake, GitHub, Python, Cloud, Data Engineering, Data Pipelines, Azure, Architecture, Databases, ETL, Snowflake
Azure Data Engineer
2021 - 2023
BP
- Created notebooks using PySparkSQL and DataFrames that take data from a Databricks database with raw data, transform them, and put them into a clean Databricks database.
- Developed Azure Data Factory (ADF) pipelines and DBT models to move data from Databricks tables into internal tables in Azure Synapse and the Snowflake database.
- Used ADF pipelines to control and schedule the ETL process flow.
- Contributed to the migration process, moving code from an old cloud architecture to a new standardized ETL architecture.
Technologies: Azure Databricks, Azure Synapse, Azure Data Lake, PySpark, Python, Cloud, Data Engineering, Data Pipelines, Azure, Architecture, Databases, ETL
Azure Data Engineer
2020 - 2021
BCBS Kansas City
- Designed an ETL/ELT solution to move data from Azure Data Lake to an Azure SQL data warehouse.
- Created a dynamic process to load data from multiple files into a staging area in Azure SQL using operations tables and a few dynamic Azure Data Factory pipelines.
- Developed SQL view and stored procedure components that will be called from an Azure Data Factory pipeline to upsert records into the data model.
- Handled all code tasks developed by the offshore development team.
Technologies: Azure Data Lake, Azure SQL, Azure Data Factory (ADF), Cloud, Data Engineering, Data Pipelines, Azure, Architecture, Databases, ETL
Data Engineer
2019 - 2020
Ensono
- Built solutions using Azure functions, Python, Azure Data Factory, Azure Synapse Analytics, and Power BI.
- Created source to target mappings and architecture documents for multiple projects.
- Created a cost estimating model for a big data modern architecture.
- Created migration plans for moving VMs from on-premise to the cloud.
Technologies: Azure, Azure Data Factory (ADF), Transact-SQL (T-SQL), Azure Data Lake, SQL Stored Procedures, Azure Databricks, ETL Development, ETL Implementation & Design, ETL Testing, Data Engineering, Data Pipelines, Architecture, Databases
ETL Consultant
2019 - 2019
Tier 1
- Created a source to target mappings to load data from multiple sources to a new SQL Server database.
- Created the operational framework used to track on-load processes.
- Used SSIS as the ETL tool to load data into the data warehouse.
- Set up SQL Agents to automatically run the ETL process.
Technologies: SQL, Azure Analysis Services, Azure DevOps, Azure Data Factory (ADF), ETL Development, ETL Implementation & Design, ETL Testing, Data Engineering, Data Pipelines, Databases, ETL
Azure Data Architect
2018 - 2019
Barilla
- Created a new enterprise data warehouse solution using Azure SQL Server as the database.
- Set up Integration run-time environment to load data from on-premise sources to the Azure cloud environment.
- Used ADF to load data into Azure blob storage to be used by data scientists.
- Used Azure Data Factory to load data from SAP BW source system to the new data warehouse.
Technologies: SAP Business Warehouse (BW), Azure Analysis Services, Azure SQL, Azure Data Factory (ADF), SQL Stored Procedures, ETL Development, ETL Implementation & Design, ETL Testing, Data Pipelines, Architecture, Databases, ETL
Senior Data Architect Consultant
2008 - 2018
Perficient Inc
- Created a completely new ETL Architecture to load data from multiple medical record systems (Epic, Quadromed, and Envision) into the IBM Atomic Warehouse Model called the Gateway.
- Took the gateway architecture and ported over to the Azure cloud platform using Azure Data Factory and stored procedures.
- Led teams of five to ten resources in implementing the above solutions.
- Create ETL Architecture documents for multiple projects.
- Developed 100's of SSIS packages to load data warehouses in SQL Server.
- Developed SSAS cubes as well as reports using SSRS.
Technologies: User Stories, Healthcare, SQL, Subversion (SVN), Shell Scripting, Service, Analysis, Microsoft SQL Server, SQL Server Integration Services (SSIS), Netezza, Datastage, SQL Stored Procedures, Azure Databricks, Azure Synapse, ETL Development, ETL Implementation & Design, ETL Testing, Architecture, Data Modeling, Databases, ETL
Experience
HCL
Azure Data Factory, Azure SQL, Azure Analysis Service
Education
1993 - 1998
Bachelor of Science Degree in Computer Engineering
University of Illinois - Chicago, IL
Skills
Libraries/APIs
PySpark
Tools
IBM InfoSphere (DataStage), IBM Information Management System, Subversion (SVN), SSAS, Microsoft Power BI, GitHub
Languages
SQL, Transact-SQL (T-SQL), Perl, Python, Snowflake
Paradigms
ETL, ETL Implementation & Design, Agile, Azure DevOps
Platforms
Azure, Azure Synapse, Databricks, Unix
Storage
Microsoft SQL Server, Azure SQL, SQL Stored Procedures, Data Pipelines, Databases, SQL Server Integration Services (SSIS), Netezza, SQL Server 2016, Data Lakes, Azure SQL Databases, Datastage
Industry Expertise
Healthcare
Other
Data Warehousing, Data Warehouse Design, Azure Data Factory (ADF), Azure Data Lake, Data Engineering, ETL Development, ETL Testing, Unix Shell Scripting, Shell Scripting, Data Analysis, Azure Databricks, Data Modeling, Azure Analysis Services, SAP Business Warehouse (BW), Analysis, Service, User Stories, Cloud, Architecture, DataFrames
Collaboration That Works
How to Work with Toptal
Toptal matches you directly with global industry experts from our network in hours—not weeks or months.
1
Share your needs
Discuss your requirements and refine your scope in a call with a Toptal domain expert.
2
Choose your talent
Get a short list of expertly matched talent within 24 hours to review, interview, and choose from.
3
Start your risk-free talent trial
Work with your chosen talent on a trial basis for up to two weeks. Pay only if you decide to hire them.
Top talent is in high demand.
Start hiring