Data/BI Architect (Big Data, AI, Machine Learning, SQL)

Job Description:
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