Position: Data Architects/Engineers
Location: 189 Harry S Truman Parkway, Annapolis, MD 21401 (Hybrid – 2 Days Remote & 3 days Onsite)
Duration: Long Term Contract
Interview: Video
Summary
The Hybrid Data Architects/Engineers will provide Data Warehouse Architect/Engineer services to serve as the primary resource(s) responsible for designing and building a data warehouse solution and working with conventional data warehouse technologies to devise plans that support designing data warehouse solutions in alignment with the Maryland Judiciary’s initiatives.
Responsibilities
- Participation in all aspects of DW and ETL process design, creation, and specification for components.
- Providing the following services in coordination with technical, functional and management representatives from JIS and the AOC.
- Source Data Model to DW Logical Design ERD
- Understanding the general structure of the MDEC data and star schema models currently in use by JIS, and any related data sources identified as a result of initial planning and assessments.
- Creating a logical warehouse data design.
- Collaboration with platform administration team, design an ETL process to move data from the source system to the data warehouse, including, but not limited to, the following:
- Outlining the ETL process, setting the borders of data processing.
- Providing system architecture for each element and the whole data pipeline.
- Documenting the requirements of the system, manage its development and facilitate necessary knowledge transfer.
- Assisting in the actual development/implementation of ETL tools.
- Conducting testing of the tools and data pipelines.
- DW Schema
- Developing effective DW model(s) representing the data entities of the logical design based on functional analytic, reporting and bulk data requirements.
- DW Physical Design
- Collaborating with platform administration to assist their efforts in creating a DW Physical design including technical considerations for data quality and operational efficiency.
- Collaborating with business and technology stakeholders to ensure data warehouse architecture development and utilization.
- All work completed by the proposed resource(s) shall be completed within regulatory compliance standards to protect sensitive data.
Reporting As Follows
- Weekly progress report on programs and project,
- Weekly report communicating project progress and status,
- Weekly time reporting on JIS provided forms, and
- Any additional reports as assigned by the supervising manager.
Skills, Experience, & Capabilities - Offeror shall propose resource(s) possessing the following preferred skills, experience, and capabilities:
- Database and analytical skills.
- Ability to query source data.
- Knowledge and experience with ETL tools, Visual Studio, and transmitting and reconstructing Extensible Markup Language (XML) and Structured Query Language (SQL).
- Knowledge of scripting languages, such as Python, and the ability to automate repetitive tasks in Azure.
- Strong analytical, consultative, and communication skills; as well as the ability to make good judgment and work with both technical and business personnel.
Ability To
- Work productively and maintain effective working relationships with peers, end users, vendor development staff, and all levels of management and Judicial personnel.
- Critically think and problem solve,
- Provide excellent communication and mentoring needs,
- Quickly evaluate, learn and prototype new technologies.
- Write optimized SQL queries and manage databases, as Azure data analysts frequently interact with Azure SQL database and other SQL-based services.
Experience With - BI best practices, relational structures, dimensional data modeling, structured query language (SQL) skills, data warehouse and reporting techniques.
- Dimensional modeling, STAR schema design, Snow fake schema design, slowly changing dimensions, confirmed dimensions.
- Designing and building BI solutions by monitoring and tuning queries and data loads, addressing user questions concerning data integrity, data mapping, monitoring performance and communicating functional and technical issues.
- Designing and implementing database models, schemes, and databases to support efficient data storage, retrieval, and analysis.
- Monitoring and optimizing data systems, data lifecycle, and infrastructure to ensure performance, scalability, and integrity.
- Designing and implementing ETL procedures for intake of data from multiple source systems; as well as ensure data quality and cleansing is verified.
- Normalization process
- Performing the design and extension of data marts, meta data, and data models.
- Ensuring all data warehouse architecture codes are maintained in a version control system.
- Advanced experience with technologies such as SQL Server 2016 or above, as well as with Azure data factory, SSIS and stored procedures
- Advanced experience developing codes, testing for quality assurance, administering RDBMS.
- High proficiency in dimensional modeling techniques and their applications
- Azure’s architecture in order to structure optimized data workflows.
- The following tools:
- Power BI
- Tableau
- Azure Synapse
- Azure Data Factory
- Azure Blob Storage
- Azure Databricks
- Microsoft Fabric
- One Lake
