Senior Data Engineer - CR 12/11/26

MARGO
Warsaw, Poland
Remote

Who this role is best for

Aimed at experienced data engineers with a focus on Azure and data product development who thrive in collaborative environments.

Best fit for

  • Candidates with 6+ years of data engineering experience and a track record in Azure Data Platform technologies
    — “6+ years of experience in data engineering”
  • Individuals who have led technical design reviews and promoted engineering excellence through code reviews
    — “Promote engineering excellence through code reviews and design reviews.”
  • Professionals skilled in building data products using PySpark, SQL, and Azure Data Factory
    — “Implement scalable, reliable and reusable data pipelines using Azure Data Factory and Apache Airflow.”

Things to consider

  • The role requires a contract commitment and likely involves hands-on production support responsibilities
    — “Provide support to the Run/Operations team for production pipelines”
  • Candidates must be prepared to participate in incident management and post-mortems
    — “Participate in incident management, root cause analysis, and post-mortems.”

How to stand out

  • Highlight your experience with Medallion Architecture and data product delivery in your resume and interviews
    — “create/extend data products following the Medallion Architecture layers”
  • Emphasize your ability to optimize data workloads for performance and cost efficiency
    — “Optimize performance, cost, and reliability of data workloads.”
  • Demonstrate your ability to refine business requirements and collaborate with POs during interviews
    — “work closely with POs to refine business requirements and transform business needs”
Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Building scalable and reliable data pipelines
  • Developing data transformations in Databricks
  • Optimizing performance and reliability of data workloads
Typical background
6+ years of experience in data engineering

Skills & requirements

Required

Azure Data FactoryApache AirflowAzure DatabricksMedallion ArchitectureEtl/elt Design PatternsData ModellingData WarehouseData LakeData LakehouseMetadata-driven Architecture

Preferred

Reporting And BI Tools

Stack & domain

Python (pyspark)SQLAzure Data FactoryApache AirflowDatabricksUnity CatalogPower BITableauData ModellingData WarehouseData LakeData LakehouseMedallion ArchitectureMetadata-driven ArchitectureEtl/eltPartitioningOptimizationPerformanceBatch And Streaming PipelinesLeadershipCommunicationProblem-solvingTeamworkData EngineeringCloudData Architecture

About the role

Original posting from MARGO via Lever

We are looking for a Senior Data Engineer to help drive the evolution of our Azure-based Data Platform and Lakehouse architecture.

This role is focused on Data Products development. The successful candidate will build pipelines in ADF, DAGs in Airflow and work closely with POs to refine business requirements and transform business needs into reliable Data Products in Databricks.

Key Responsibilites:

Hands-on Data Product development

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Implement scalable, reliable and reusable data pipelines using Azure Data Factory and Apache Airflow.

-

Develop data transformations in Azure Databricks (PySpark / SQL) to create/extend data products following the Medallion Architecture layers:

Bronze (raw ingestion)

Silver (cleansed & conformed)

Gold (business-ready data products)

-

Optimize performance, cost, and reliability of data workloads.

-

Raise important questions during business maturation in order to detect risks before development stage.

Technical Leadership

-

Participate in architecture reviews and technical decision-making. 

-

Promote engineering excellence through code reviews and design reviews.

-

Collaborate with Architects, Product Owners in data product technical maturation.

Support & Operations (Run Team Collaboration)

-

Provide support to the Run/Operations team for production pipelines and data products for complex topics.

-

Troubleshoot and resolve data incidents, failures, and performance issues

-

Participate in incident management, root cause analysis, and post-mortems.

-

Ensure proper handover, documentation, and operational readiness of developed solutions.

-

Contribute to improving runbooks, monitoring, and operational processes.

Compensation:

Technical Skills Required

6+ years of experience in data engineering

Strong technical expertise with:

Python (PySpark)

SQL (advanced level)

Hands-on experience with Azure-based Data Platform including:

Databricks

Unity Catalog

Apache Airflow

Azure Data Factory

Reporting and BI tools (Power BI, Tableau or similar)

Solid understanding of data modelling fundamentals, main architectures and design patterns

Data Warehouse, Data Lake and Data Lakehouse architectures

Medallion architecture

Metadata-driven architecture

ETL/ELT design patterns

Understanding of:

Partitioning, optimization, and performance

Batch and streaming pipelines

Source: MARGO careers (Lever)

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