Data Engineer

Exp: 6+ years

Work Mode: Hybrid (3 days work from office) or Remote can also be provided.

Key Responsibilities

• Design, develop, and maintain robust data pipelines in Hadoop and related ecosystems, ensuring data reliability, scalability, and performance.
• Implement data ETL processes for batch and streaming analytics requirements.
• Optimize and troubleshoot distributed systems for ingestion, storage, and processing.
• Collaborate with data engineers, analysts, and platform engineers to align solutions with business needs.
• Ensure data security, integrity, and compliance throughout the infrastructure.
• Maintain documentation and contribute to architecture reviews.
• Participate in incident response and operational excellence initiatives for the data warehouse.
• Continuously learn mindset and apply new Hadoop ecosystem tools and data technologies.

Required Skills and Experience

• Proficiency in Hadoop ecosystems such as Spark, HDFS, Hive, Iceberg, Spark SQL.
• Extensive experience with Apache Kafka, Apache Flink, and other relevant streaming technologies.
• Proven ability to design and implement automated data pipelines and materialized views.
• Proficiency in Python, Unix or similar languages.
• Good understanding of SQL oracle, SQL server or similar languages.
• Ops & CI/CD: Monitoring (Prometheus/Grafana), logging, pipelines (Jenkins/GitHub Actions).
• Core Engineering: Data structures/algorithms, testing (JUnit/pytest), Git, clean code.
• 5+ years of directly applicable experience
• BS in Computer Science, Engineering, or equivalent experience.