Data Architect

We are looking for a Data Architect to help us support our continued growth. The Data Architect is responsible for leading aspects of our data practice and owning the overall data architecture for client projects as well as recommending best practices based on client needs. The Data Architect facilitates discovery sessions to understand client business, applications and data and translates findings into technical requirements supported by a documented design.

They provide input and communication to project and client team members in order to build the foundation as a trusted partner. They lead the implementation team through all phases of the life cycle; including design, build, test, deploy and maintenance.

During the project selling phase:

• Participate in business development activities to showcase Coastal skills in the data disciplines, including architecture, modeling, migration, integration, data quality and enrichment, security, analytics, master data management, metadata management, big data and governance
• Assist with demonstrations of client work and internal accelerators to reinforce our experience with prospects
• Assist in developing statements of work and accurate estimates for the data related work being proposed

During the planning and analysis phase:

• Bring knowledge of data architecture options to the project team and propose solutions that will properly meet the business needs at hand
• Provide input on the best components to include in the enterprise architecture, including all Salesforce clouds (i.e. Sales, Service, Health Cloud, FLS, CPQ/QTC, Heroku, Mule Soft, etc.), as well as non-Salesforce infrastructure such as GCP, AWS or Azure, and how to integrate these cloud offerings with a client’s on-prem or private cloud systems.
• Identify when a data migration will be necessary to retire a legacy system or seed required data to a new system
• Lead source data analysis for data migrations and produce mappings and transformation instructions to reach the target database
• Assess the need for data quality tools to assist in de-duplication, merging and validation (i.e. addresses, email, phone numbers, etc.)
• Identify when data enrichment requirements necessitate a service to be added to the architecture
• Identify when a proper analytics and visualization platform is necessary to meeting business reporting and analytics requirements
• Know when to apply the appropriate integration patterns in the architecture; including batch/ETL, event triggered, durable message queues, API proxies, screen embedding, etc.
• Awareness of security best practices into all aspects of the data architecture
• Assist in the design of the appropriate architecture based on time, scope and budget constraints - have the ability to simplify as necessary while still addressing the needs of the business requirements

During the implementation phase:

• Provide assistance in data modeling to the project team
• Guide the team on the appropriate phases of the implementation to perform conceptual, logical or physical modeling
• Guide the team on the appropriate time to normalize vs. denormalize a data model based on technology, use case and performance requirements
• Be fluent at relational, and dimensional data modeling techniques
• Provide detailed artifacts from the data modeling process, including Entity Relationship Diagrams (ERDs) and comprehensive data dictionaries
• Contribute to the implementation of all tools identified during the planning phase, including tools for integration, migration, quality, enrichment, analytics, visualization, master data, metadata and security
• During the testing phase:
• Assist in identifying best practices for data in all phases of testing, including unit, system, integration, performance/stress, user acceptance, and regression
• Introduce testing tools to ensure high quality and repeatable steps
• Provide guidance on test data creation and maintenance to ensure all edge cases are tested with production-like data
• Assist putting measures in place when sensitive production data is needed for testing, including obfuscation and/or masking

During the deployment phase:

• Identify tooling to ensure high quality and repeatable deployment activities take place
• Provide assistance in using the Salesforce metadata and tooling APIs
• Provide assistance with using version control tools, such as Git Hub, to manage code repositories and deployment pipelines
• Recommend the use of Salesforce metadata deployment tools such as the SFDX, CLI, Copado, Gear Set, Flosum, or other relevant tooling
• In support of Coastal’s people, methods and tools:
• Develop and document best practices in all areas of the data discipline
• Mentor our novice analysts, data engineers and new architects to develop skills and promote interest in the data career path
• Develop and advocate for accelerators in all areas of data to help our teams deliver more consistently and efficiently
• Provide input for the improvement of our estimating models in the data disciplines
• Assist in nourishing vendor…