Data/BI Architect - Pontiac, MI

DTS is looking for Data/BI Architect for our direct client Position in Pontiac, MI

Data / BI Architect

** Data Business Intelligence (BI) Architect role is a hybrid of data architecture, engineering & business strategy, bridging the gap between tech data solutions & business objectives. 

** Designs, develops & maintains the overall data strategy ensuring the County data in scope is accessible, reliable & secure for analysis and decision-making. 

** The right candidate has experience in architecting data solutions that can be used for descriptive, diagnostic, predictive & prescriptive analytic solutions. 

KEY RESPONSIBILITIES: 

Stakeholder Collaboration: Work closely with business & IT stakeholders to gather req & translate business needs into tech specifications, including identification of data sources. 

Data Arch Design & Data Modeling: Architect & implement scalable, secure & efficient data solutions, including data warehouses, data lakes, and/or data marts. Design conceptual, logical & physical data models. 

Tool and Platform Selection: Evaluate, recommend & implement tools aligned with recommended architecture, including visualization tools aligned with business needs. 

ETL/ELT Pipeline Mgt: Design, develop & test data pipelines, integrations to source mgt & ETL / ELT processes to move data from various sources into the data warehouse. 

Data Catalog & Metadata Mgt: Design, create & maintain an enterprise-wide data catalog, automating metadata ingestion, establishing data dictionaries, and ensuring that all data assets are properly documented & tagged. 

Data Governance and Discovery: Enforce data governance policies through the data catalog, ensuring data quality, security & compliance. Enable self-service data discovery for users by curating & organizing data assets in an intuitive way. 

Performance Optimization: Monitor & optimize BI systems & data pipelines to ensure high performance, reliability & cost-effectiveness. 

Technical Leadership: Provide technical guidance & mentorship across the organization, establishing best practices for data mgt & BI development.

Environment: Role incl. defining data platform tech stack. 

Example tech below; not required to have experience in all. 

Data Platforms: DW & lake concepts incl. dimensional modeling & cloud services (S3, AWS Redshift, RDS, Azure Data Lake Storage, Synapse Analytics, BigQuery, Databricks, Snowflake, Informatica); 

Databases: SQL & relational/non-relational (SQL Server, Oracle, PostgreSQL, MongoDB); 

BI Tools: Power BI, Business Objects, Tableau, Crystal, Looker; 

ETL/ELT: Cloud native (AWS Glue, Azure Data Factory, Google Cloud Dataflow) & in-warehouse transform tools (Fivetran, Talend, dbt); 

Big Data Tech: Hadoop, Spark, Kafka; 

Programming/API: Python, Keras, Scikit-learn, R, XML; 

ML/DL/Analytic Engines: TensorFlow, PyTorch, Trillium, Apache Spark;

Modeling Tools: MS Visio, ER/Studio, PowerDesigner; Source systems incl. on-prem, cloud, & SaaS;