Data platform engineer in lakehouse architecture

💙 Capitole is growing fast, and we want you to be part of the journey! We are looking for a Senior Data Platform Engineer with +6 years of experience to help drive the evolution of our Azure-based Data Platform and Lakehouse architecture . This role is focused on the platform itself . The professional will own and evolve the foundations that data product teams build on: Apache Airflow orchestration (migrating from ADF) , Azure resource management (Key Vault, identity and access, networking, storage), Azure DevOps CI/CD and Infrastructure as Code

• Own the Apache Airflow platform: environments, deployment, upgrades, configuration, connections, variables, pools and DAG standards.
• Work on the migration from Azure Data Factory to Airflow and the evolution of the Metadata-Driven Orchestration Framework (DAG generation, reusable operators, dependency and scheduling patterns).
• Ensure Airflow is reliable and observable: SLAs, alerting, retries, backfills, health monitoring and clear failure ownership.
• Manage Azure resources with Infrastructure as Code (Terraform): Databricks workspaces, Data Lake Storage, Data Factory, Key Vault, networking and supporting services.
• Own secrets and identity management: Key Vault, service principals and managed identities, secret scopes and rotation.
• Own access management: Azure RBAC, Entra ID groups, Unity Catalog grants and ownership, following least privilege, plus access requests and periodic reviews.
• Own Azure DevOps: repositories, CI/CD pipelines, branch policies and multi-environment promotion, including deployment validation and Terraform state.
• Track cost and governance of Azure resources: tagging, budgets, right-sizing and cost attribution (e.g. query tagging).
• Contribute to the implementation of the Data Catalog and Data Quality Framework and it’s lineage across the platform.
• Drive observability: pipelines that are observable, debuggable and alert-driven, with clear ownership of failures.
• Operate the Databricks platform: Unity Catalog structure, cluster and job policies, Auto Loader ingestion patterns, and performance and cost optimization of workloads.
• Participate in architecture reviews and technical decision-making, stating trade-offs (performance, cost, reliability, complexity) with data.
• Define and promote engineering standards: naming conventions, patterns and guidelines, through code reviews and design reviews.
• Collaborate with Architects, Product Owners and data engineers in technical maturation of data products.
• Build and maintain developer tooling and automation, including AI-assisted engineering workflows (shared agent instructions, skills, automated PR review).
• Provide second-line support to the Run/Operations team for complex production topics.
• Troubleshoot and resolve platform incidents, failures and performance issues; lead root cause analysis and post-mortems.
• Ensure proper handover, documentation and operational readiness of platform changes.
• Continuously improve runbooks, monitoring and operational processes.

• 6+ years of experience in data engineering, with significant time on platform or infrastructure topics
• Strong technical expertise with Python and SQL (advanced), including PySpark and Delta Lake semantics
• Deep hands-on experience with Apache Airflow in production: DAG design, deployment, operations, upgrades, and orchestration of Databricks and ADF workloads
• Hands-on experience with Azure resource management: Key Vault, managed identities and service principals, secret management
• Access management: Azure RBAC, Entra ID, Unity Catalog permissions
• Azure DevOps (repos, pipelines, service connections, environments) and CI/CD for data platforms
• ADLS, networking and security basics, Azure Data Factory
• Infrastructure as Code (Terraform) and multi-environment promotion
• Hands-on experience with Databricks and Unity Catalog (compute, jobs, governance)
• Observability and monitoring, alerting and incident management
• Solid understanding of Data Lakehouse architecture, Medallion architecture and metadata-driven architecture; awareness of cost management and performance
• Strong problem-solving and analytical thinking
• Ability to work in cross-functional teams and to influence without authority
• Ownership mindset and attention to detail
• Good communication skills with both technical and business stakeholders: leads with the recommendation, quantifies, and is transparent about uncertainty
• Будет плюсом: Led an Airflow implementation or migration (ideally from ADF), or run it at scale; Built metadata-driven orchestration or reusable ETL frameworks; Built developer tooling or LLM-agent workflows (MCP, skills, automated review) for engineering teams; Applied FinOps practices on Azure and Databricks: cost attribution, budgets, forecasting and measurable savings; Experience running Airflow on Kubernetes or operating containerized workloads on AKS

• €1,200/year for your professional development (trainings, events, certifications…)
• Monthly feedback sessions with your team to keep learning and growing
• Private health insurance fully covered by Capitole
• Payflow benefits (meal, transport, childcare vouchers)
• Wellhub subscription
• Discounts with top brands through Capitole Club
• Team buildings every two months (our summer party and Christmas dinner are legendary!)
• Football, padel, and basketball teams sponsored by Capitole
• Tech communities where sharing knowledge is part of our DNA
• And above all… an AMAZING TEAM that you’ll love being a part of!