WHAT THIS ROLE WILL DO Solution Design: Develop comprehensive data warehouse and platform architecture blueprints, encompassing data modeling, ETL processes, data integration, storage, and data governance.

In addition, the candidate should also have some hands-on experience working with the Azure platform and primarily: Azure Data Warehouse / Synapse, Azure Data Factory, Azure Data Lake, Databricks and Azure Analysis Services.

Experience Using airflow at scale, with integration to meta-data and lineage systems of record. Strong experience with Snowflake including snowsql, snow pipes, user authentication & Authorizations, Warehouse management, Storage integration etc.

Experience with Data warehouse architecture and ETL integration (Snowflake, Postgres, Oracle, SQL Server, Matillion ETL). Set design patterns for application integration, data governance, and analytics development.

Experience working with cloud-oriented data warehouse, data platform, and data lake technologies (e.g. Snowflake, Redshift), including data pipeline development and data engineering.

Minimum 10 years of designing and implementing an operational production grade large-scale data solution on Microsoft Azure Snowflake Data Warehouse. Strong understanding or Snowflake on Azure Architecture, design, implementation and operationalization of large-scale data and analytics solutions on Snowflake Cloud Data Warehouse.

3+ years of development experience with cloud services (e.g. AWS / Azure) utilizing various support tools (e.g. EC2, ECS, S3, Kinesis, VMs, Blob, Cosmos, Data Factory, SQL Data warehouse, ARM Templates, Event Hubs.

Experience with modern data warehouse concepts and tools (Snowflake, Azure Data Lake, Databricks) Experience with modern data integration technologies (Snowflake, Azure Data Factory, Informatica, DBT, HVR.

Data Integration: SSIS, Azure Data Factory, Databricks, or other enterprise ETL tools; + in architecture, design and development of data integration (ETL) solutions, including data quality and master data management - primarily using Microsoft technologies.

Knowledge of Data Warehouses/Lakehouse architectures, Master Data Management, Data Quality Management, Data Integration, and Data Warehouse architecture.

Strong experience with various Data Management architectures like Data Warehouse, Data Lake, Data Hub and the supporting processes like Data Integration, Governance, Metadata Management.

Extract and analyze data using various software packages including, but not limited to, Microsoft Excel, SPSS, Oracle SQL Developer, Argos, Collin College Student Information System (Banner) and the Collin College Data Warehouse (Zogotech), Workday, R and other tools as needed.

Preference for experience in one or more emerging big data technologies such as Hadoop, Cassandra, MongoDB and associated data integration tools like Kafka and Nifi. Experience with data visualization platforms like Microsoft Power BI or Tableau is also a plus.

Knowledge of technical writing skills; ability to produce professional reports that effectively communicate ideas using appropriate words, correct grammar, punctuation, spelling and effective integration of quantitative and visual information using the APA style guide for reports and references.

ETL/Data integration/Streaming – Talend, DataBricks, Python, Spark, Kafka, Informatica. Cloud Lake and Warehouse – Snowflake, S3 Data Lake, other comparable technologies. Drive architecture in one or more areas of data storage (Data Lakes and Warehouses), data integration, Business Intelligence and analytics.