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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
We're looking for a 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.
Responsibilities:
Requirements:
Job ID: 128606637
Skills:
Apache Airflow, Spark, Apache Beam, Python, Data Platform Management, Data Layer Design, dbt, Google Cloud Ecosystem, Google Cloud Services, Data Pipeline Development
Skills:
data engineering , Data Transformation, Power Bi, Data Modeling, Sql, ELT, Git, Microsoft Azure, Python, Etl, Azure DevOps, table maintenance, data quality checks, OneLake, data pipelines, schema validation, Spark notebooks, cloud data platforms, ADF pipelines, Lakehouse tables, Microsoft Fabric
Skills:
BigQuery, Hadoop, Pyspark, Data Warehousing, Bash, Sparksql, Dataproc, Sql, Cloud Storage, Hive, Gcp, Iam, DataFlow, Python, Airflow, DataFrame, Pub Sub
Skills:
Java, Hive, Hadoop, Scala, Spark, Nodejs, Emr, Python, Sql, AI code generation tools
Skills:
data engineering , snowflake , Cassandra, Postgres, Python, Azure DevOps, AWS, Hadoop, Scala, Big Data, Dataproc, Redshift, Sql, Git, Hive, Gcp, Spark, Data Warehousing, MongoDB, DataFlow, Azure, Aws S3, Airflow, DataMart Design, Google BigQuery, Data Lakes, GCS