Vacancy expired!
Overview
This AVP Cloud Data Domain will help lead a data transformation to support data science, analytics and business teams. Data Domains are a distinct reflection of how we do business. The Data Domains are logical groupings of data that represent business characteristics in order to create a shared understanding. Critical data elements are captured, curated and maintained, while analytics and reporting utilize this information to accelerate insights to drive decision-making. The AVP Cloud Data Domains will blend a passion for data and analytics, while mastering critical enterprise data for GM Financial. In this position, you will manage and control the tactical execution of data, ingestion through consumption, to power the data and analytics platform. In this Agile environment, the AVP Cloud Data Domain will partner with business and technical leaders to influence strategic decisions, delivery and execution of specific data products. The AVP Cloud Data Domain will ensure that products are available in the cloud data platform to both business and technical requirements. This role will ensure alignment of products and work through ongoing planning and prioritization of the enterprise backlog. The AVP will ensure that the data domains are scalable and secure to meet our future growth and requirements. The AVP will have a passion for building agile teams that effectively plan and execute work and collaborate with broader cross-functional teams to successfully deliver mission-critical cloud data projects. The AVP will build partnerships with business subject matter experts, cloud data architects, cloud data engineers and enablement teams to scale our enterprise data and analytics platform. Responsibilities JOB DUTIES- Build and sustain a high-performing team of full stack cloud data engineers and data domain subject matter experts
- Collaborate with key business and technical leaders to execute data and analytics vision and strategy
- Lead requirements gathering and implementation of Data Domain(s) capabilities roadmap
- Prepare business users for change due to implementation of new technical and data solutions
- Devise and track project KPIs and success measures, for example - adoption, engagement, quality, utilization
- Utilize expertise in technology and business operations to ensure data solutions are aligned to drive strategy and impact
- Partner with Analytics teams to empower the business with new Data Domains
- Drive business intelligence and analytics best practices with data - agile, repeatable, automated, data pipelines and engineering
- Translate broad strategies into specific data domain plans, utilizing existing resources and information to achieve strategic objectives and improve business results
- Collaborate with Data Leadership to define cloud data domains and Data & Analytics priorities and goals
- Collaborate with Leadership on department's performance to ensure accountability for achieving business results
- Collaborate on the flow of data from transactional systems, data management and master data layer, to the cloud data and analytics platform with business definitions, requirements and transformations in the data domain
- Coach, mentor, and train cloud data domain team members to establish quality, accuracy, accountability and compliance
- Champion an environment that promotes trust, continuous improvement, innovation, quality outcomes and self-development
- Develop relationships with key customer business and technical decision makers: drive long-term cloud data adoption through an enterprise data stewardship program within the company; enable cloud data advocacy
- Share insights and best practices, and connect with teams to remove key blockers
- Perform other duties as assigned
- Conform with all company policies and procedures
- Advanced knowledge of cloud data life cycle automation that includes source to consumption data ingestion, validation, versioning, meta-data, lineage, retention, purge and archiving of critical data elements to support analytical teams and business outcomes
- Advanced knowledge of cloud data engineering to support data domain modeling
- Advanced knowledge of cloud and data security methodologies, policies, standards and best practices
- Advanced knowledge of best practices in cloud data governance for regulatory landscape for financial institutions
- Advanced knowledge of python, SQL,Databricks and PySpark to create data solutions
- Advanced knowledge of data engineering solutions in open-source tools and languages in AWS, Google and/or Azure
- Advanced knowledge of creating cloud MDM, CDC, Data Lineage, Metadata Management solutions
- Advanced knowledge of developing and optimizing data pipelines with business rules and transformation logic
- Advanced knowledge of event driven data architecture, engineering and operations in the cloud
- Extensive experience developing cloud data solutions for Marketing, CX, Data Science, Finance, Treasury and customer360
- Extensive experience with Data Design and Curation to support Advanced Analytics (ML, Risk, AI)
- Extensive experience with traditional RDBMS (Oracle, Teradata, DB2)
- Extensive knowledge of Agile SAFe
- Advanced working knowledge of information systems and operations
- Extensive experience working with transactional, temporal, time series, structured and unstructured data in the cloud
- Effective written and verbal presentation skills with an ability to communicate complex technology, architecture, tools, processes and solutions with senior management
- Ability to interact collaboratively with internal customers and external vendors on highly complex enterprise cloud data and platform strategies
- Demonstrated ability to effectively lead, motivate, challenge, organize and supervise a team of cloud data engineers
- Demonstrated quantitative skills and ability to apply complex cloud data operations to business rules and requirements
- Demonstrated expertise in leading distributed teams of data engineers to align on key architectural and technical decisions and direction - and guiding those through successful execution
- Experience architecting large sophisticated data systems with high volume and high-performance requirements in the cloud
- Proven cloud knowledge and understanding of data operations and services - data factories, service bus, storage, lakes, dw
- Ability to orchestrate, lead, and influence teams, ensuring successful implementation of cloud data projects
- Bachelor's Degree in the field of Computer Science/Engineering, Analytics, Data Science, Mathematics or related discipline required
- Master's Degree in the field of Computer Science/Engineering, Analytics, Data Science, Mathematics or related discipline preferred
- 7-10 years leadership experience in collaborating with the business to build enterprise scale cloud data solutions to support machine learning, artificial intelligence and analytics required
- 5-7 years experience in managing data engineering, data operations, IT, analytics teams or equivalent required
- 5-7 years of cloud data development solutions, PaaS, SaaS, IaaS, Serverless, Data Orchestration, API Management, microservice frameworks, container orchestration required
- 3-5 years experience with SAFe agile for cloud data engineering and transformation required
Vacancy expired!