Principal Architect - Databricks

About Tiger Analytics

Shape the Future of AI. Transform the World's Leading Businesses.

Tiger Analytics is one of the fastest-growing AI services firms, partnering with some of the world's largest and most influential organizations to redefine how business gets done. We help Fortune 500 companies harness the power of Artificial Intelligence, Generative AI, Data Science, Data Engineering and Advanced Analytics to solve their most complex challenges, unlock new growth opportunities, and create lasting business impact.

We are at the forefront of the AI revolution, helping enterprises move beyond traditional analytics to embrace Generative AI, agentic AI, intelligent automation, and cloud-native data platforms. A global presence across North America, Latin America, Europe, and India.

At Tiger Analytics, we don't just help businesses adapt to the future—we help them build it.

What you will be doing

We are looking for an experienced Principal Architect – Databricks to lead the architecture and design of enterprise-scale data platforms and Lakehouse solutions. The ideal candidate will bring deep expertise in Databricks, modern data engineering, cloud data platforms, and enterprise data architecture, along with the ability to translate complex business requirements into scalable, secure, and cost-effective solutions.

Key Responsibilities

• Enterprise Data Architecture: Define end-to-end data architectures and technical roadmaps using Databricks and cloud data platforms to support enterprise data engineering, analytics, and AI workloads.
• Lakehouse Architecture: Design scalable Lakehouse solutions using Delta Lake, medallion architecture, and modern data management patterns.
• Solution Architecture & Design: Lead architecture assessments, solution design, technology evaluations, and proof-of-concept initiatives aligned with business and technical requirements.
• Data Engineering: Establish architectural standards for batch and streaming data pipelines using Apache Spark, PySpark, Spark SQL, and other relevant data processing technologies.
• Cloud Data Platforms: Design and integrate Databricks solutions with cloud-native storage, compute, networking, security, and data integration services.
• Platform Modernization: Lead data platform modernization and migration initiatives involving legacy data warehouses, on-premises platforms, and cloud-based data ecosystems.
• Performance & Cost Optimization: Define best practices for Spark optimization, workload management, compute utilization, storage optimization, and overall platform cost efficiency.
• Security & Governance: Establish enterprise data security and governance standards using Unity Catalog, access controls, data lineage, auditing, and data quality practices.
• DataOps & Engineering Standards: Define standards for CI/CD, automated testing, infrastructure as code, deployment automation, monitoring, and production support.
• Architecture Governance: Review solution designs, guide technical decisions, establish reusable architectural patterns, and ensure adherence to enterprise standards.
• Client & Stakeholder Engagement: Partner with client stakeholders and senior technology leaders to understand business priorities, present architecture recommendations, and drive consensus on solution design.
• Technical Leadership: Mentor architects and engineering teams, provide technical direction, and contribute to solution proposals, estimations, and strategic technology initiatives.
• Analytics & AI Enablement: Architect data platforms that support business intelligence, advanced analytics, machine learning, and generative AI use cases.

Requirements

What we need

• 15+ years of overall experience in data engineering, data architecture, or related technology roles, with significant experience in architecture and solution design.
• Strong hands-on expertise in Databricks architecture and enterprise implementation.
• Proven experience designing and implementing Lakehouse architectures using Delta Lake and modern data engineering patterns.
• Strong knowledge of Apache Spark, PySpark, Spark SQL, distributed computing, and large-scale ETL/ELT pipelines.
• Experience architecting cloud-based data platforms, including cloud storage, data integration, orchestration, security, and identity management.
• Strong understanding of enterprise data architecture, data modeling, data warehousing, data governance, and data quality.
• Experience with Unity Catalog, data access controls, lineage, and enterprise security practices.
• Knowledge of CI/CD, DevOps/DataOps, infrastructure as code, automated testing, and production deployment practices.
• Demonstrated ability to lead architecture reviews, evaluate technology choices, and define scalable, reliable, and cost-effective solutions.
• Strong client-facing communication, stakeholder management, consulting, and technical leadership skills.
• Experience mentoring technical teams and guiding complex enterprise implementation initiatives.

Benefits

Why Join Tiger Analytics:

• Drive High-Impact Business Transformation: Lead strategic engagements that go beyond traditional analytics, delivering enterprise-wide AI adoption, cloud-native data modernization, and measurable business outcomes.
• Build and Lead at Global Scale: Collaborate with exceptional AI, data, engineering, and consulting talent across geographies to deliver transformative solutions and grow strategic client partnerships.
• Benefits: Medical, Dental, Vision, Retirement Accounts, Long and Short Term Disability, Life Insurance, HSA/FSA Accounts (USA) and Discretionary time-off.
• Continuous Learning & AI Upskilling: Stay ahead of the rapidly evolving AI landscape through continuous learning, hands-on exposure to emerging technologies, and opportunities to build expertise in Generative AI, agentic AI, and next-generation data platforms. Grow alongside a team that invests in developing future-ready skills and encourages innovation.

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.