Role Summary: The IT Data Domain Architect is responsible for defining and presenting a shared data analytics integration architectural vision for the enterprise in partnership with Decision Sciences Business Unit, Enterprise Architecture, and other IT development teams, defining solution architecture and technical context diagrams in alignment to business/technology strategy of being a data driven organization. A key component of this role is the ownership of the solution-level analytics integration, information, and technology strategies and alignment of these strategies to enterprise strategy, processes and organization. Solution-level strategies define the guiding principles and goals of how the enterprise will utilize and consume data. Role Responsibilities: Strategic Work
Educate and advise team members about technology solutions and emerging trends
Continually participate in visioning exercises and contribute to the overall data analytics strategy
Understands requirements for analytics integration to drive strategic goals
Contributes to the development of tactical and long-term, strategic roadmaps partnership with Enterprise Architecture team and the Decision Sciences Business Unit.
Leads, promotes and communicates architecture progress, outcomes and results
Understands and implements the governing principles that guide data analytics integration, which includes partnership with Data Governance and Information Risk Management.
Supports the IT Data Operations and Analytics team to ensure compliance with the enterprise architecture standards, quality of code, alignment to metrics/targets.
Ensures data integration developers have appropriate knowledge, experience, tooling, environments, and support to become a robust team.
Gains a solid understanding of other business units data integration needs to ensure future support and transfer of knowledge
Operational Work
Applies continuous improvement of data analyti4cs integration development quality, efficiency and speed, through processes such as TDD, scrums, iterative deployments, and other innovations that lead to improved results
Participates in capturing technical requirements including Non-Functional Requirements per project, product, system, or application.
Solve and resolve production issues
Responsible for minimizing expenditures and optimizing the utilization technology investments. Assists in the budgeting process by providing forecast data
Facilitate / participate in code reviews
Continually refine and document data integration best practices
Identifies and quantifies risk, makes recommendations for risk mitigation and contingency plans. Advance anticipated risk to management accurately.
Collaborate with team members on data integration designs and alternatives
Work within and across Agile teams to craft, develop, test, implement, and support data analytics integration solutions.
Report on status of products and projects on a regular and timely basis.
Ensure the timely resolution of issues.
Follow VCI standards and guidelines.
Required –
10+ years in data analytics integration experience (design, develop, code, test, support)
Minimum of 3-5 years proven technical solution architecture experience in addition to development experience in the area of Financial Services (Automotive Finance a plus) passionate about analytics data integration solutions and platforms.
Education: Required –
B.S. in Computer Science or related field.
Desired –
Advanced Degree a plus
General Skills:
Must be a great teammate. We not Me.
Solid understanding and experience in both agile and traditional project development methodologies.
Entrepreneurial approach identifying future technology enablement to support business strategy
Experience crafting technical blueprints, modeling as-is and to-be architectures for data analytics integration based on business requirements
Ability to articulate the relationship between business strategy and technology strategy
Work closely EA team to align to roadmaps, strategy, designs, standards, guidelines, and governance.
Propose new technical standards/guidelines/patterns and adhere to them. Ensure that designs are performant, scalable, resilient, and align to appropriate recoverability pattern.
Keep the technical footprint current (fitness assessment, technical debt, application health etc.)
Ensure alignment and collaboration with Enterprise wide Architecture
Experience delivering clear and concise executive-level presentations to advise business and IT leadership of status, risks, and issues while driving consensus on decisions.
Aptitude for assessing sophisticated IT programs and selecting appropriate sourcing strategies to procure needed external project resources.
Financial skills: cost/benefit analysis of technology recommendations – experience assembling comprehensive software development estimates.
Knowledge of data integration technologies from an architecture direction standpoint and from an experienced implementation perspective
Good interpersonal communication skills (both written and verbal).
Negotiation and conflict resolution skills; ability to create an open environment where conflicts as to project priorities, scope and requirement decisions can be aired and resolved in an objective manner
Proven capability to work on several projects simultaneously
Analytical and conceptual thinking – using logic and reason, creative and strategic
Integration – joining people, processes or systems
Results oriented
Intermediate to Advanced skills in Microsoft Office (Excel, Word and PowerPoint)
Experience with MS Office 365 a plus
Specialty Skills: Required–
Demonstrated expertise in data analytics integration solutions, working with structured methodologies and development of various work including Data Warehouse, Operational Data Store, Data Lake and various Business Intelligence Solutions.
Experience in data integration solutions, such as extract transform and load (ETL), orchestration and API development and the various platforms available (cloud and on prem). Examples include Informatica, Biztalk, Mulesoft, Jitterbit, etc
Expertise in big data engineering, building metadata, driving pipeline, real-time and batch ingestion, and ML OPS
Thorough understanding of master and reference data; data quality and associated processes that maintain these foundational and certified data sets
Experience with data quality or MDM software solutions like: Informatica IDQ or MDM.
Expertise in metadata concepts, data lineage and data mapping. Previous experience with software solutions that support these constructs.
Expert level proficiency in structured query language (SQL), Python
Thorough understanding of relational data models including third normal form and fact / dimension designs
Proficient in open source integration technologies; ability to properly design and structure big data; examples include Hadoop, Hive, Hue, Impala, Spark and Kafka
KanBan and Agile methodologies
Desired–
Modern development practices – e.g. DevOps
Experience with open source database platforms such as MySQL and MariaDB
Solid understanding of analytical tools such as SAS, R and Python.
Cloud development on AWS using various platform features such as Kinesis / Firehose, Glue, Redshift, S3, Lambda, SDK, API Gateway, etc …
