Full Job Description
Senior Data Software Engineer/ AI Agents, Azure, Spark
We are looking for an experienced Senior Data Software Engineer with strong hands-on expertise in Azure and the Spark ecosystem , primarily focused on building and maintaining data transformation pipelines. The candidate should be comfortable with any Spark-adjacent technology (PySpark, Spark SQL, Scala Spark, Databricks, Synapse, etc.) rather than being locked into one specific flavor. Experience with Microsoft Fabric is a strong plus but not a requirement. The ideal candidate combines great technical skills with leadership capability, contributing to architecture, design, development, and mentoring of engineering teams - preferably in complex enterprise or financial services environments.
Responsibilities
Lead the design, development, and optimization of scalable data engineering solutions on Azure, using Spark-based processing (PySpark, Spark SQL, Scala, or equivalent)
Own end-to-end data transformation pipelines, including ingestion, transformation, storage, and analytics
Work with Azure-native data services such as Data Factory, Databricks, and Synapse
Support high-performance data access patterns using Cosmos DB (NoSQL API) where applicable
Collaborate with data scientists, AI engineers, and product stakeholders to enable data-driven analytics and insights
Mentor and guide junior engineers, setting coding standards and best practices
Ensure data quality, security, governance, and performance across platforms
Contribute to technical decision-making and solution architecture discussions
Requirements
3+ years of experience in data engineering roles, preferably within complex enterprise or financial services environments
Expertise in Azure cloud data services, including Data Factory, Databricks, and Synapse
Proficiency in the Spark ecosystem, including PySpark, Spark SQL, and Scala Spark
Background in designing and maintaining end-to-end data transformation pipelines covering ingestion, transformation, storage, and analytics
Skills in ensuring data quality, security, and governance across large-scale platforms
Capability to contribute to solution architecture and technical decision-making
Competency in mentoring engineering teams and setting coding standards and best practices
Understanding of high-performance data access patterns using Cosmos DB (NoSQL API)
English proficiency at an Upper-Intermediate level (B2) or higher
Nice to have
Hands-on experience with Microsoft Fabric and OneLake (Delta / OpenLake)
Familiarity with financial instruments and financial services data
Exposure to AI-assisted development tools such as GitHub Copilot and awareness of industry-standard LLMs
Knowledge of Data Science fundamentals and collaboration experience with DS teams