Appnovation Technologies
VeevaVaultTechnicalBusinessAnalyst
Neural analysis suggests this role is
optimal for Senior candidates.
“Veeva Vault Technical Business Analyst at Appnovation Technologies. Skills: Data engineering, Cloud-native data ecosystems, Advanced data modeling, AI/MLOps readiness, Full-stack solution delivery, System reliability & resilience (SRE), Architectural leadership. Manage the 'discovery-to-scale' pipeline. Identify recurring patterns in the field”
What You'll Achieve.
Deliver high-impact results; Deliver tangible business results; Optimize data engineering workflows; Support the deployment and governance of AI/ML models; Prioritize solution speed and business value; Ensure graceful degradation; Drive post-incident improvements
Industry & Context.
Problem discoverer; Turning ambiguity into clear problem statements
What They're Looking For.
Must Have
Bachelor's degree in Computer Science or Engineering, 8–12 years of relevant experience leading and delivering complex data engineering projects with multi-team or business impact, Proven expertise in designing, building, and maintaining robust, scalable data pipelines (ETL/ELT), Ability to navigate complex enterprise data landscapes, effectively handle undocumented schemas, and implement resilient integration solutions for high-volume data, Deep expertise in deploying and managing data infrastructure on cloud platforms (AWS, Azure, or GCP), Proficient in Infrastructure as Code (Terraform/CloudFormation), Establishing end-to-end CI/CD pipelines for data solutions, Advanced skills in conceptual, logical, and physical data modeling, Ability to balance data normalization, query performance, and safely manage complex schema migrations in production, Mastery of incorporating AI tools to optimize data engineering workflows, Ability to design data validation and evaluation frameworks that support the deployment and governance of AI/ML models, Capability to rapidly prototype and build complete, end-to-end data applications across diverse technology stacks, Prioritizing solution speed and business value while effectively managing technical debt, Direct experience defining and monitoring service level objectives (SLOs/SLIs), Track record of designing highly resilient data systems that ensure graceful degradation and driving post-incident improvements, Ability to make sound architectural trade-offs, Design scalable system components, Produce high-quality, well-tested code that adheres to enterprise standards
Nice to Have
Kubernetes a plus
What You'll Do.
Manage the 'discovery-to-scale' pipeline
Identify recurring patterns in the field
Hand off validated solutions to Platform Engineers for enterprise generalization
Bridge the gap between building technical products and solving real-world business problems
Rapid solution delivery
Deep domain immersion
Design and build data integration
and infrastructure that enable analytics and AI capabilities
Define your own direction within strategic goals
Influence multiple teams
Navigate high complexity and ambiguity to deliver tangible business results
Deploying and managing data infrastructure on cloud platforms
Establishing end-to-end CI/CD pipelines for data solutions
Safely manage complex schema migrations in production
Incorporate AI tools to optimize data engineering workflows
Design data validation and evaluation frameworks
Rapidly prototype and build complete
end-to-end data applications
Prioritize solution speed and business value
Effectively manage technical debt
Define and monitor service level objectives (SLOs/SLIs)
Design highly resilient data systems
Ensure graceful degradation
Drive post-incident improvements
Make sound architectural trade-offs
Design scalable system components
well-tested code that adheres to enterprise standards
Bridge gaps between engineering
Rapidly immerse yourself in new domains to speak the language of the business
Seek out ambiguity rather than avoiding it
Drive team curiosity through challenging questions
Create an environment that encourages experimentation
Drive an accountability culture focused on business impact rather than just deliverables
Own relationships and make trade-offs between custom solutions and generalizable work
Map complex system interactions across technical and business domains
Anticipate cascading effects and understand how technology changes impact operations
Translate seamlessly between technical and business language
Ensure requirements are clear enough to enable AI generation and facilitate productive discussions with stakeholders
Embed with users to discover latent needs
Turn ambiguity into clear problem statements rather than waiting for defined tasks
How You'll Work.
Team & Collaboration
Influence multiple teams; Collaborative and innovative work environment; Work with Platform Engineers; Facilitate productive discussions with stakeholders
Communication Scope
Precise communicator; Translate seamlessly between technical and business language
Process & Methodology
Leading and delivering complex data engineering projects
Full Job Description
About us Appnovation is a global, full-service digital partner that combines Strategy, Experience & Design, Engineering and Managed Services. We build digital solutions that deliver real impact today and serve as foundations for future growth. Bold ambition. Practical action. Endless possibilities. About the Role Join forces with Appnovation to deliver high-impact results for one of our key strategic partners - a global leader in their field. This engagement offers a unique vantage point into a world-class organization with exceptional opportunities for professional growth and long-term career advancement As a Senior Data Engineer, you will manage the "discovery-to-scale" pipeline, identifying recurring patterns in the field and handing off validated solutions to Platform Engineers for enterprise generalization. In this forward-deployed role, you will bridge the gap between building technical products and solving real-world business problems through rapid solution delivery and deep domain immersion. Your primary objective is to design and build data integration, storage systems, and infrastructure that enable analytics and AI capabilities. This role requires high-level autonomy, where you will define your own direction within strategic goals, influence multiple teams, and navigate high complexity and ambiguity to deliver tangible business results. What we are looking for Experience & Education: Bachelor's degree in Computer Science or Engineering with 8–12 years of relevant experience leading and delivering complex data engineering projects with multi-team or business impact. Enterprise Data Integration & Architecture: Proven expertise in designing, building, and maintaining robust, scalable data pipelines (ETL/ELT). Must demonstrate the ability to navigate complex enterprise data landscapes, effectively handle undocumented schemas, and implement resilient integration solutions for high-volume data. Cloud-Native Data Ecosystems: Deep expertise in deploying and manag
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