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 ResponsibilitiesThought 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.
Pre-Sales and Business Development
- 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.
Data & Insights Practice Leadership
- 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.
Requirements- 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.
Preferred Qualifications- 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.
BenefitsSignificant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging, and entrepreneurial environment with a high degree of individual responsibility.
