Data Engineer

About Delhivery:

Delhivery is India's leading fulfillment platform for digital commerce. With a vast logistics network spanning 18,000+ pin codes and over 2,500 cities, Delhivery provides a comprehensive suite of services including express parcel transportation, freight solutions, reverse logistics, cross-border commerce, warehousing, and cutting-edge technology services. Since 2011, we've fulfilled over 550 million transactions and empowered 10,000+ businesses, from startups to large enterprises.

Vision : To become the operating system for commerce in India by combining world-class infrastructure, robust logistics operations, and technology excellence.

About the Role: Data Engineer / Sr. Data Engineer/Lead Data Engineer:

We're looking for a Lead Data Engineer/ Sr. Data Engineer / Data Engineer who can design, optimize, and own our high-throughput data infrastructure. Are you a passionate Kafka and Kafka Connect ecosystem data engineer looking for an exciting opportunity to work on cutting-edge big data projects Look no further! Delhivery is seeking a talented and motivated Streaming Data Engineering Expert to join our dynamic team.

Are you a passionate Spark and Scala developer looking for an exciting opportunity to work on cutting-edge big data projects Look no further! Delhivery is seeking a talented and motivated Spark & Scala Expert to join our dynamic team.

Responsibilites:

• Develop and optimize Spark applications to process large-scale data efficiently.
• Collaborate with cross-functional teams to design and implement data-driven solutions.
• Troubleshoot and resolve performance issues in Spark jobs.
• Stay up-to-date with the latest trends and advancements in Spark and Scala technologies.

Requirements:

• Proficient in Redshift, data pipelines, Kafka, Real time streaming,etc.
• Strong experience with Apache Spark, Spark Streaming, and Spark SQL.
• Solid understanding of distributed systems, Databases, System design, and big data processing frameworks.
• Familiarity with Hadoop ecosystem components (HDFS, Hive, HBase) is a plus.