Description

Job Description:-

• Engineer and optimize data pipelines using solutions like Apache Hudi, Apache Trino, Azure ADLS
• Strong hand-on experience in Python
• Collaborate cross-functionally with product, analytics, and AI teams to ensure data is a strategic asset
• Senior Data Engineer with at least 10 years of professional experience in software or data engineering, including a minimum of 4 years focused on data pipelines (batch and streaming).
• Proven experience driving technical direction and mentoring engineers while delivering complex, high-scale solutions as a hands-on contributor
• Strong understanding of event-driven architectures and distributed systems, with hands-on experience implementing resilient, low-latency pipelines
• Practical experience with cloud platforms (AWS, Azure, or GCP) and containerized deployments for data workloads
• Fluency in data quality practices and CI/CD integration, including schema management, automated testing, and validation frameworks (e.g., dbt, Great Expectations)
• Operational excellence in observability, with experience implementing metrics, logging, tracing, and alerting for data pipelines using modern tools
• Solid foundation in data governance and performance optimization, ensuring reliability and scalability across batch and streaming environments
• Proven experience with Lakehouse architectures and related technologies, including Apache Hudi, Azure ADLS Gen2, HDFS, and other big data technologies (Trino, Databricks, Spark)
• Strong collaboration and communication skills, with the ability to influence stakeholders and evangelize modern data practices within your team and organization

Key Skills

Education

Any Graduate