💙 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, Databricks and Unity Catalog governance, observability and cost efficiency, while remaining hands-on and close to the teams that use the platform.
🔵 Responsibilities:
Orchestration Platform (Apache Airflow & ADF)
· 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.
Azure Resource Management
· 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).
Hands-on Data Platform evolution
· 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.
Technical Leadership
· 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).
Support & Operations (Run Team Collaboration)
· 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.
🔵 Requirements:
Technical Skills
· 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:
o Key Vault, managed identities and service principals, secret management
o Access management: Azure RBAC, Entra ID, Unity Catalog permissions
o Azure DevOps (repos, pipelines, service connections, environments) and CI/CD for data platforms
o 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
Soft Skills
· 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
🔵 What we’re looking for in you:
· 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
💙 Why you'll love working with us
At Capitole, we believe our people are our greatest strength. That's why we offer:
💙Life at Capitole
Want to learn more about us? capitole-consulting.com
See what our teams are saying about us: Glassdoor Reviews
💌 Ready to take the next step?
Send us your profile – we can’t wait to meet you!
The employee will adhere to information security policies: