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 recent 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.
Valuable understanding of SQL oracle, SQL server or similar languages.
Ops & CI/CD: Monitoring (Prometheus/Grafana), logging, pipelines (Jenkins/Git Hub 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.

📌 Data Engineer Bengaluru (India)
🏢 ACL Digital
📍 India