Omm IT Solutions
Data Architects/Engineers
Omm IT Solutions, Annapolis, Maryland, United States, 21403
Job DescriptionPlease Note: This is a Hybrid Position with two days remote and 3 days onsite.
About the Position:
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 Client's initiatives.
Candidate shall be responsible for the following:
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 Client and the AOC.Source Data Model to DW Logical Design ERDUnderstanding the general structure of the MDEC data and star schema models currently in use by Client, 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 SchemaDeveloping effective DW model(s) representing the data entities of the logical design based on functional analytic, reporting and bulk data requirementsDW Physical DesignCollaborating 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 architecturedevelopment and utilization.All work completed by the proposed resource(s) shall be completed within regulatory compliancestandards 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 Client provided forms, andAny additional reports as assigned by the supervising manager.Key Required Tools/Skills:
Power BITableauAzure SynapseAzure Data FactoryAzure Blob StorageAzure DatabricksMicrosoft FabricOne LakeRequirements
Basic Qualifications and Skills:
Candidate should be possessing the following preferred skills, experience, and capabilities:
Bachelor's degree with at least 5 years of experienceDatabase 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 processPerforming 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 proceduresAdvanced experience developing codes, testing for quality assurance, administering RDBMS.High proficiency in dimensional modeling techniques and their applicationsAzure's architecture in order to structure optimized data workflows.
About the Position:
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 Client's initiatives.
Candidate shall be responsible for the following:
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 Client and the AOC.Source Data Model to DW Logical Design ERDUnderstanding the general structure of the MDEC data and star schema models currently in use by Client, 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 SchemaDeveloping effective DW model(s) representing the data entities of the logical design based on functional analytic, reporting and bulk data requirementsDW Physical DesignCollaborating 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 architecturedevelopment and utilization.All work completed by the proposed resource(s) shall be completed within regulatory compliancestandards 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 Client provided forms, andAny additional reports as assigned by the supervising manager.Key Required Tools/Skills:
Power BITableauAzure SynapseAzure Data FactoryAzure Blob StorageAzure DatabricksMicrosoft FabricOne LakeRequirements
Basic Qualifications and Skills:
Candidate should be possessing the following preferred skills, experience, and capabilities:
Bachelor's degree with at least 5 years of experienceDatabase 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 processPerforming 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 proceduresAdvanced experience developing codes, testing for quality assurance, administering RDBMS.High proficiency in dimensional modeling techniques and their applicationsAzure's architecture in order to structure optimized data workflows.