Role: Sr. Data Engineer (PySpark, Azure, Databricks)

Work type: Full remote (from Romania)

Collaboration type: employment contract or B2B contract

Role Objective

• Design, develop and maintain scalable data pipelines within a modern cloud-based data platform

• Contribute to the development of a Lakehouse architecture leveraging Azure technologies and

Databricks for advanced analytics and AI-driven use cases

Key Responsibilities

• Design and implement scalable data pipelines using Azure Fabric

• Develop data processing and transformation logic using Python, PySpark and SparkSQL

• Work with OneLake and Delta Lake concepts to support modern Lakehouse data architectures

• Develop and support solutions using Cosmos DB (NoSQL API)

• Contribute to Azure Fabric workloads including Data Engineering, Data Factory Gen2 and Lakehouse

• Build and optimize Spark workloads using Databricks

• Implement CI/CD pipelines and follow DevOps best practices

• Integrate data solutions with Power BI for reporting and analytics

• Collaborate with AI, data science and product teams to enable data-driven and AI-powered solutions

• Ensure data quality, performance, reliability and security across data platforms

• Participate in Agile ceremonies and contribute to sprint deliveries

• Support production environments and contribute to continuous improvements

Technical Skills

• 5+ years of experience in Data Engineering or related engineering roles

• Strong hands-on experience with Azure Fabric

• Proficiency in Python

• Solid experience with PySpark and SparkSQL

• Experience with Batching

• Experience with Spark Streaming

• Hands-on experience with OneLake / Delta Lake (OpenLake concepts)

• Knowledge of DF Gen2 and M-code

• Experience with CI/CD pipelines (Azure DevOps or equivalent)

• Good understanding of Azure services

• Experience integrating data solutions with Power BI

Nice-to-Have Skills

• Experience with code generation, including non-AI and AI-assisted approaches

• Expertise with Cosmos DB and variants (Mongo, Cassandra, Table APIs)

• Exposure to Azure AI Foundry

• Experience with Data Science workflows

• Strong background in Big Data and Spark ecosystems

• Knowledge of financial instruments and financial services data

• Hands-on experience with industry-standard LLMs (including GPT, Claude, or similar)

Qualifications

• University degree in Computer Science, Engineering, Information Systems or related field

• Strong understanding of modern data platforms and big data ecosystems

• Experience working in Agile development environments

• Ability to work independently and collaboratively in distributed teams

Competencies

• Strong analytical and problem-solving skills

• Excellent communication and collaboration abilities

• Results-oriented mindset

• Adaptability and continuous learning mindset

• Attention to detail and quality

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