Technology Partner - Databricks

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.

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.

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.

• 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.

Significant 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.

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.