Architect - Enterprise Data Operations

• Governs data design/modeling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned.
• Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting.
• Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools.
• Advocates existing Enterprise Data Design standards; assists in establishing and documenting new standards.
• Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development.
• Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework.
• Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives, maximizes reuse.
• Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper management: business and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations.
• Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development.
• Assist with data planning, sourcing, collection, profiling, and transformation.
• Create Source To Target Mappings for ETL and BI developers.
• Show expertise for data at all levels: low-latency, relational, and unstructured data stores; analytical and data lakes; data streaming (consumption/production), data in-transit.
• Develop reusable data models based on cloud-centric, code-first approaches to data management and cleansing.
• Partner with the data science team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders.
• Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization.

Qualifications:

• 6+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools.
• 6+ years of experience developing enterprise data models.
• 6+ years in cloud data engineering experience in at least one cloud (Azure, AWS, GCP).
• 6+ years of experience with building solutions in the retail or in the supply chain space.
• Expertise in data modelling tools (ER/Studio, Erwin, IDM/ARDM models).
• Fluent with Azure cloud services. Azure Certification is a plus.
• Experience scaling and managing a team of 5+ data modelers
• Experience with integration of multi cloud services with on-premises technologies.
• Experience with data profiling and data quality tools like Apache Griffin, Deequ, and Great Expectations.
• Experience with at least one MPP database technology such as Redshift, Synapse, Teradata, or Snowflake.
• Experience with version control systems like GitHub and deployment & CI tools.
• Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus.
• Experience of metadata management, data lineage, and data glossaries is a plus.
• Working knowledge of agile development, including DevOps and DataOps concepts.
• Familiarity with business intelligence tools (such as PowerBI).

Skills, Abilities, Knowledge:

• Excellent communication skills, both verbal and written, along with the ability to influence and demonstrate confidence in communications with senior level management.
• Proven track record of leading, mentoring, hiring and scaling data teams.
• Strong change manager. Comfortable with change, especially that which arises through company growth.
• Ability to understand and translate business requirements into data and technical requirements.
• High degree of organization and ability to manage multiple, competing projects and priorities simultaneously.
• Positive and flexible attitude to enable adjusting to different needs in an ever-changing environment.
• Strong leadership, organizational and interpersonal skills; comfortable managing trade-offs.
• Foster a team culture of accountability, communication, and self-management.
• Proactively drives impact and engagement while bringing others along.
• Consistently attain/exceed individual and team goals
• Ability to lead others without direct authority in a matrixed environment.

Differentiating Competencies Required

• Ability to work with virtual teams (remote work locations); lead team of technical resources (employees and contractors) based in multiple locations across geographies
• Lead technical discussions, driving clarity of complex issues/requirements to build robust solutions
• Strong communication skills to meet with business, understand sometimes ambiguous, needs, and translate to clear, aligned requirements
• Able to work independently with business partners to understand requirements quickly, perform analysis and lead the design review sessions.
• Highly influential and having the ability to educate challenging stakeholders on the role of data and its purpose in the business.
• Places the user in the center of decision making.
• Teams up and collaborates for speed, agility, and innovation.
• Experience with and embraces agile methodologies.
• Strong negotiation and decision-making skill.
• Experience managing and working with globally distributed teams.