Databricks Architect

Company Description Tiger Analytics is a global consulting and services firm that helps organizations navigate complexity through data and AI-led transformation. The company partners with clients to design and operationalize solutions that deliver measurable business value at scale, leveraging deep expertise in value chains, agile operating models, and modern data platforms. With strong strategic partnerships across major cloud hyperscalers, Tiger Analytics builds cutting-edge, customized Data & AI solutions instead of relying solely on standard approaches. The team comprises over 5000 technologists and consultants working on challenging real-world problems. Tiger Analytics offers opportunities across offices in the US, India, Canada, Mexico, UK, Spain, Singapore, and Australia.
Role Description This is a full-time, on-site Databricks Architect role based in Bengaluru/Hyderabad/Chennai. The Databricks Architect will design and implement scalable data architectures on Databricks, including lakehouse solutions, data pipelines, and integration with enterprise data platforms. The role involves collaborating with data engineers, data scientists, and business stakeholders to translate requirements into robust technical designs and best practices. The architect will oversee implementation, performance optimization, security, and governance for Databricks workloads, and provide technical leadership and guidance to project teams. Responsibilities also include documenting architecture, supporting project planning, and contributing to standards, templates, and reusable components that improve delivery efficiency and quality.
Qualifications
Strong skills in Architecture and Architectural Design for large-scale data and analytics platforms, preferably on Databricks.
Experience in Software Development, including building and optimizing data pipelines using Python, SQL, and Spark.
Proficiency in Integration of Databricks with cloud data services, APIs, ETL tools, and enterprise systems.
Demonstrated Project Management capabilities, including coordinating cross-functional teams and managing technical delivery milestones.
Hands-on experience with Databricks, Spark, and at least one major cloud platform (Azure, AWS, or GCP).
Knowledge of data warehousing, lakehouse architectures, data modeling, and performance tuning.
Understanding of data security, governance, and compliance in cloud environments.
Ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders.
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Previous experience in consulting or client-facing data/AI projects is an advantage.

Work arrangement
No