Real job — pulled straight from Margo’s careers page · Verified November 14, 2026 · No reposts.
Job description
Margo is hiring a Senior Data Platform Engineer — a full-time, based in Warsaw role. Apply directly on Margo's careers page below.
Senior Data Platform Engineer CR 12/11/26
Team: Polska Team
Location: Warsaw
Commitment: Permanent contract & B2B
Workplace Type: remote
Salary:
Technical Skills
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6+ years of experience in data engineering, with significant time on platform or infrastructure topics
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Strong technical expertise with Python and SQL (advanced), including PySpark and Delta Lake semantics
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Deep hands-on experience with Apache Airflow in production: DAG design, deployment, operations, upgrades, and orchestration of Databricks and ADF workloads
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Hands-on experience with Azure resource management:
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Key Vault, managed identities and service principals, secret management
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Access management: Azure RBAC, Entra ID, Unity Catalog permissions
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Azure DevOps (repos, pipelines, service connections, environments) and CI/CD for data platforms
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ADLS, networking and security basics, Azure Data Factory
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Infrastructure as Code (Terraform) and multi-environment promotion
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Hands-on experience with Databricks and Unity Catalog (compute, jobs, governance)
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Observability and monitoring, alerting and incident management
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Solid understanding of Data Lakehouse architecture, Medallion architecture and metadata-driven architecture; awareness of cost management and performance
Soft Skills
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Strong problem-solving and analytical thinking
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Ability to work in cross-functional teams and to influence without authority
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Ownership mindset and attention to detail
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Good communication skills with both technical and business stakeholders: leads with the recommendation, quantifies, and is transparent about uncertainty
We are looking for a Senior Data Platform Engineer 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.
Key Responsibilities
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Own the Apache Airflow platform: environments, deployment, upgrades, configuration, connections, variables, pools and DAG standards.
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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).
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Ensure Airflow is reliable and observable: SLAs, alerting, retries, backfills, health monitoring and clear failure ownership.
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Manage Azure resources with Infrastructure as Code (Terraform): Databricks workspaces, Data Lake Storage, Data Factory, Key Vault, networking and supporting services.
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Own secrets and identity management: Key Vault, service principals and managed identities, secret scopes and rotation.
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Own access management: Azure RBAC, Entra ID groups, Unity Catalog grants and ownership, following least privilege, plus access requests and periodic reviews.
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Own Azure DevOps: repositories, CI/CD pipelines, branch policies and multi-environment promotion, including deployment validation and Terraform state.
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Track cost and governance of Azure resources: tagging, budgets, right-sizing and cost attribution (e.g. query tagging).
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Contribute to the implementation of the Data Catalog and Data Quality Framework and it’s lineage across the platform.
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Drive observability: pipelines that are observable, debuggable and alert-driven, with clear ownership of failures.
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Operate the Databricks platform: Unity Catalog structure, cluster and job policies, Auto Loader ingestion patterns, and performance and cost optimization of workloads.
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Participate in architecture reviews and technical decision-making, stating trade-offs (performance, cost, reliability, complexity) with data.
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Define and promote engineering standards: naming conventions, patterns and guidelines, through code reviews and design reviews.
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Collaborate with Architects, Product Owners and data engineers in technical maturation of data products.
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Build and maintain developer tooling and automation, including AI-assisted engineering workflows (shared agent instructions, skills, automated PR review).
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Provide second-line support to the Run/Operations team for complex production topics.
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Troubleshoot and resolve platform incidents, failures and performance issues; lead root cause analysis and post-mortems.
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Ensure proper handover, documentation and operational readiness of platform changes.
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Continuously improve runbooks, monitoring and operational processes.
Orchestration Platform (Apache Airflow & ADF)
Azure Resource Management
Hands-on Data Platform evolution
Technical Leadership
Support & Operations (Run Team Collaboration)
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Frequently asked questions
What skills are required for Senior Data Platform Engineer at Margo?
The required skills for Senior Data Platform Engineer at Margo include: Python, SQL, Spark, Airflow, Databricks, Azure, Azure DevOps, Terraform, CI/CD.
What is the seniority level for Senior Data Platform Engineer at Margo?
Senior Data Platform Engineer at Margo is a Senior level position.
How do I apply for Senior Data Platform Engineer at Margo?
You can view the full description and apply for Senior Data Platform Engineer at Margo on EchoJobs: https://echojobs.io/job/margo-senior-data-platform-engineer-cr-12-11-26-bv4wj.