Job Opportunities API

Do you want to boost your career and collaborate with expert, talented colleagues to solve and deliver against our clients' most important challenges? We are growing and are looking for people to join our team. You'll be part of an entrepreneurial, high-growth environment of 300.000 employees. Our dynamic organization allows you to work across functional business pillars, contributing your ideas, experiences, diverse thinking, and a strong mindset. Are you ready? About your role Enterprise AI is forcing organisations to rethink their data estates. Traditional reporting platforms are no longer enough for GenAI and AI-driven decision-making. Clients need data that is trusted, governed and consumable by both people and intelligent systems. As a Databricks Architect , you will help clients transform fragmented data into AI-ready lakehouse platforms. You’ll advise on architecture across Databricks and cloud ecosystems, covering data products, governance, metadata, lineage, semantic layers and GenAI data patterns. This is a client-facing consulting role . You will solve ambiguous problems, shape architecture decisions, and communicate clearly with both technical teams and senior stakeholders. Working in cross-functional teams, you’ll deliver target architectures, platform assessments, data product designs, governance models and implementation roadmaps. We’re hiring across levels. Junior roles focus on delivery and platform expertise; senior roles require enterprise thinking, stakeholder influence and leadership. We’re looking for strong data architects with depth in areas such as Databricks/lakehouse architecture, governance, semantic modelling, data products, metadata or GenAI (e.g. RAG) . Requirements 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. Skills and Qualifications:  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 Given that this is just a short snapshot of the role we encourage you to apply ev