Technology Partner - Databricks
Indexed description
The Technology Partner is a multi-faceted leadership role within Tiger's core Data & Insights Solutions practice. This individual will bring both breadth and depth of technology expertise, with a demonstrated track record of delivering large-scale transformations, leading innovation-driven practices, and consulting with and managing executive stakeholders across IT and business functions.
Key Responsibilities
Thought Leadership and Client Engagement
- Liaise with data and technology leaders across strategic client organizations to provide forward-looking advisory services and thought leadership
- Lead brown-bag sessions, workshops, and educational forums to share relevant data, AI, cloud, and platform perspectives with core clients
- Conduct proactive reviews of client data platforms, operating models, and technology practices; provide improvement recommendations, solution approaches, and transformation roadmaps
- Provide technology leadership for Data & Insights transformation agendas spanning technology, organization, operating processes, and governance
- Help recruit and assess key technology talent for critical client-facing roles
- Create detailed, scalable technology solutions for first-of-a-kind, complex, and enterprise-wide initiatives
- Present Tiger's Data & Insights capabilities to prospective clients and executive stakeholders
- Develop solution architectures, proposals, statements of work, and responses to client requirements
- Partner with business and delivery leaders to shape data, analytics, AI/ML, cloud, and modernization opportunities
- Mentor engineering, data, architecture, and analytics talent at multiple career levels
- Manage and guide architecture resources across client engagements and internal initiatives
- Develop thought-leadership content for go-to-market offerings, including reference architectures, methods, accelerators, and delivery practices
- Participate in interviews and help evolve hiring, assessment, and talent-development practices
- Partner with offshore counterparts on solution design, training, delivery quality, and overall capability development
- 10+ years of experience developing solution architectures for large enterprises and complex transformation programs
- Databricks expertise is a core requirement, including hands-on and architectural experience designing, implementing, and modernizing enterprise data and AI platforms using the Databricks Lakehouse Platform
- Demonstrated experience with Databricks capabilities such as Delta Lake, Apache Spark, Databricks SQL, Unity Catalog, Workflows, notebooks, data pipelines, governance, security, and platform administration
- Experience building and governing data engineering, analytics, machine learning, and AI workloads on Databricks, including batch processing, real-time streaming, and scalable data pipeline architectures
- Experience integrating Databricks with cloud services, particularly within Azure and Azure Databricks environments; experience with AWS Databricks or Databricks on Google Cloud is a plus
- Strong knowledge of traditional and modern data platforms, including NoSQL, MPP, columnar databases, big data ecosystems, cloud data warehouses, and cloud-native data platforms
- Experience with cloud data platform services across Azure, including Azure Data Lake Storage, Azure Data Factory, Synapse Analytics, Event Hubs, and related integration, security, and monitoring services
- Experience with data-processing tools and frameworks covering batch ETL/ELT, real-time streaming, event-driven architectures, IoT data pipelines, and distributed computing
- Databricks certification, such as Databricks Certified Data Engineer/Databricks Certified Professional/ Data Engineer/Databricks Certified Machine Learning Professional/Databricks Certified Data Analyst
- Experience leading enterprise Databricks migrations or modernization programs from legacy Hadoop, on-premises data warehouses, ETL platforms, or cloud data platforms
- Experience defining Lakehouse operating models, platform standards, reusable frameworks, governance patterns, and FinOps practices
- Strong experience working with senior client stakeholders, including CIOs, CTOs, CDOs, Heads of Data, Analytics, Engineering, and AI/ML
Disclaimer
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
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