Databricks Architect

Our Enterprise AI practice supports large global organisations to find and deliver business value from data and AI. We work within the broader Infosys ecosystem, partnering with deep industry and domain experts to identify transformational opportunities and help clients bridge from strategy through to implementation. We collaborate closely with our global delivery organisation to turn ideas into scalable solutions. Examples of our work include developing AI transformation roadmaps, setting up AI Centres of Excellence, data strategy and readiness assessments, automating complex workflows with multi-agent systems and intelligent document processing with generative AI. We always bring a human-centred and value-led approach to technology transformation.

Infosys Consulting is a globally renowned management consulting firm on the front-line of industry disruption and at the cutting edge of technology. We work with market leading brands across sectors. Our culture is inclusive and entrepreneurial. Being a mid-size consultancy within the scale of Infosys gives us the global reach to partner with our clients throughout their transformation journey.

• Strong hands-on experience with Databricks Lakehouse Platform.
• Deep knowledge of Spark, PySpark, SQL, Delta Lake, Unity Catalog, Databricks Workflows, Auto Loader, and Delta Live Tables.
• Experience designing scalable data platforms on Azure, AWS, or GCP.
• Good understanding of data engineering, data modelling, data quality, security, and governance.
• Experience with CI/CD, Terraform, Git, monitoring, and operational support.
• Strong communication skills with the ability to explain complex technical topics clearly.

Personal attributes:

• Comfortable working in ambiguous consulting environments, shaping options, making trade-offs explicit and taking senior stakeholders on the journey from strategy to implementation.
• Self-directed, able to prioritise and juggle multiple workstreams.
• Clear communicator who can simplify complexity for technical and non-technical audiences alike.
• Collaborative, curious, continuous learner.

• Design and deliver modern data lakehouse solutions using Databricks, Delta Lake, Unity Catalog, PySpark, Spark SQL, and cloud data services.
• Define end-to-end architecture covering ingestion, transformation, data modelling, governance, security, orchestration, monitoring, and consumption.
• Build reusable patterns for batch, streaming, and near-real-time data pipelines.
• Implement strong data governance using Unity Catalog, including access control, lineage, cataloguing, and data ownership.
• Work with cloud platforms such as Azure, AWS, or GCP and integrate Databricks with tools like ADF, Power BI, Purview, Snowflake, dbt, Kafka, and APIs.
• Guide teams on performance tuning, cost optimisation, cluster strategy, job scheduling, and production support.
• Drive DevOps/DataOps practices using CI/CD, Git, Terraform, Databricks workflows, and automated deployment.
• Lead architecture discussions, review solution designs, mentor engineers, and engage confidently with senior stakeholders.