Data/BI Architect

Seeking a talented consultant for our direct local govt client for a Data Business Intelligence (BI) Architect role.
This will be a hybrid of data architecture engineering & business strategy bridging the gap between tech data solutions & business objectives.
This person will design develop and maintain the overall data strategy ensuring the client 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 Architechture 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 Management: 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 Management: 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 and mentorship across the organization establishing best practices for data management & BI development.

• Data Platforms: DW & lake concepts including dimensional modeling and 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 tools
    • 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