Senior Data Software Engineer

We're looking for a hands-on Senior Data Software Engineer with strong expertise in Apache Spark and large-scale distributed computing systems. This role covers the complete data infrastructure lifecycle, from building ingestion solutions to ensuring pipelines remain reliable and scalable over time. The ideal candidate works well across teams, turning complex business needs into solid technical solutions while upholding high engineering and performance standards. Responsibilities Build and implement reliable data ingestion solutions and pipelines leveraging Cloud Native and Big Data technologies Oversee the entire technical stack, covering configuration management, monitoring, debugging, and performance optimization Create and sustain scalable data pipelines that support efficient data processing and analysis Work closely with cross-functional teams and data architects to gather business requirements and convert them into technical specs Drive code reviews and testing efforts to uphold quality standards and SDLC best practices Produce and update thorough technical documentation across data engineering projects to support transparency and knowledge transfer Diagnose and fix data-related issues quickly and effectively, ensuring solutions remain high-quality, dependable, and scalable Requirements At least 3 years of experience in Data Software Engineering with a focus on large-scale distributed systems Strong command of Python and SQL Significant hands-on background with Apache Spark, Kafka, and Airflow Working knowledge of major cloud platforms (AWS, Azure, or GCP) Familiarity with Databricks or Snowflake is a plus Hands-on expertise in tuning Apache Spark job performance Solid grasp of SDLC principles, quality gates, and Agile practices Self-driven, able to work independently, and comfortable managing multiple projects efficiently Strong communication abilities with English proficiency at B2+ level