Senior Data Engineer

Key Responsibilities

• Design, build, and maintain highly reliable, scalable, and performant data processing pipelines.
• Develop and maintain streaming and batch data systems leveraging technologies like Kafka, Spark, and Hadoop.
• Collaborate with architecture, DevOps, and analytics teams to integrate data solutions within cloud-based ecosystems (GCP, Azure).
• Apply strong software engineering practices, ensuring code quality, reusability, and system resilience.
• Implement data modeling, migration, and transformation solutions supporting data warehousing and BI initiatives.
• Integrate with orchestration tools such as Airflow or Automic to automate and optimize data workflows.

Required Skills & Experience

• Programming: Strong proficiency in Scala, Python, and Java (J2EE) for data processing and backend development.
• Big Data Technologies: Deep understanding of Hadoop, Spark, and distributed data frameworks.
• Streaming: Hands-on experience with Kafka or similar event streaming platforms.
• Cloud Platforms: Experience with Google Cloud Platform (GCP) or Microsoft Azure for data engineering and deployment.
• Data Engineering: Expertise in data modeling, data migration protocols, and data transformation processes.
• Workflow Orchestration: Practical experience with Airflow, Automic, or equivalent scheduling tools.
• Data Warehousing & BI: Familiarity with enterprise data warehouse concepts, BI tools, and performance optimization strategies.
• Best Practices: Strong focus on code quality, system reliability, scalability, and performance optimization.