Databricks Architect
On-siteWrocław, Lower Silesia, Poland
Job Summary
Databricks Architect at Infosys Consulting (Enterprise AI) is a client-facing consulting role focused on transforming fragmented data into AI-ready lakehouse platforms. You will advise on architecture across Databricks and cloud ecosystems, covering data products, governance, metadata, lineage, semantic layers and GenAI data patterns. You’ll deliver target architectures, platform assessments, data product designs, governance models and implementation roadmaps, lead architecture discussions, mentor engineers, and engage senior stakeholders in cross-functional teams. The role spans junior to senior levels and requires strong Databricks lakehouse expertise, Spark/PySpark/SQL, governance and security practices, cloud platform experience (Azure/AWS/GCP), and proficiency with CI/CD, Terraform, Git, and production support. You’ll collaborate to design scalable data platforms, guide performance tuning and cost optimisation, and drive DevOps or DataOps practices while communicating clearly with technical and non-technical audiences.
Required Qualifications
- 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.
- 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.
- Comfortable working in ambiguous consulting environments, shaping options, making trade-offs explicit and taking senior stakeholders on the journey from strategy to implementation.
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