Number of Positions:1 Threshold Band:7A RTH-Y Note: 1. This position requires the candidate to work from the office starting from day one. 2. Ensure that you perform basic validation and gauge the interest level of the candidate before uploading their profile to our system. 3. Candidate Band will be count as per their relevant experience. We will not entertain lesser experience profile for higher band. Mode of Interview: Face to Face (Mandatory). **JOB DESCRIPTION** Total Exp 7+ yrs Relevant Exp 6+ yrs Mandatory skill (Must have) Google Cloud, Data warehouse, BigQuery, BigQueryML, SQL Good to have (not necessary) Azure Data warehouse), Pyspark, Big Data fundamentals. JD (Comments to supplier) Advises on Google toolset for data engineering.  Develops data engineering solutions on Google Cloud ecosystemSupports and maintains data engineering solutions on Google Cloud ecosystem. Designs, Builds and operationalises batch and realtime data pipelines using Google cloud services - Google DataProc, DataFlow and PubSubDesigns,builds and operaionalises data layer on BigQuery, Big Table, Cloud Spanner, CloudSQL and AlloyDB Design,   Builds data migration scripts and migrates data using services – Google Data Migration Services Proficient with Google Data Platform components for Data Platform and architectures - Google Cloud Storage, BigTable, BigQuery DataProc with Spark and Hadoop, Google DataFlow with Apache Beam / PythonProficient with Google PubSub and Managed Streaming for Apache KafkaProficient with  Comfortable using other open source technologies like Apache Airflow and dbt, Spark / Python or Spark / ScalaExperience in developing batch and real time data pipelines for Data Warehouse and DatalakeExperience in Scheduling and managing the data platform on Google cloud Scheduler, Cloud Composer (Airflow) Solid experience on Object Oriented Programming using Python Good knowledge of data structures and algorithms Solid background of data engineering skills – PySpark, Big data, Hive, Sql, Kafka. Must have experience in handling Real time & Batch ingestion. Should be able to optimise Spark job performance, debug production job failures Should have hands on experience on cloud platform, preferably GCP Good to have experience building REST APIs Location Gurgaon - IBMFG2JP00017883