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Senior Consultant - Lead Pyspark Cloud Data Engineer

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Description

Job Summary
Lead PySpark Cloud Data Engineer: This job involves understand the overall requirement of the enterprise Data need and design develop the robust, highly scalable resilient data pipeline using PySpark, Dataproc, open source table formats and other Google services. Job will involve extensive interfacing co-ordination with other senior tech folks (across India US) and lead the design development of the data ingestion pipelines.


The experience we are looking to add to our team

Required
  • Bachelors degree or higher from a reputed university
  • 8 to 12 years total experience with majority of that experience related to building high performant data pipelines batch and streaming
  • Strong Hands on experience / expert-level proficiency in PySpark for data processing, transformation, and analysis
  • Extensive experience in implementing large scale data ingestion and curation solutions
  • Hands-on experience with cloud-based data platforms, preferably Google Cloud Platform (GCP) and services like Dataproc, BigQuery, and Cloud Storage
  • Knowledge in Apache Iceberg for open table formats
  • Advanced SQL skills for data querying, manipulation, and optimization
  • Proficiency with Git and collaborative development workflows
  • Excellent analytical and problem-solving skills with a keen attention to detail
  • Strong communication and interpersonal skills, with the ability to explain complex technical concepts to both technical and non-technical audiences


Good to have
  • Expertise in Google Cloud services
  • Proven experience with Apache Iceberg for open table formats and BigLake Metastore for unified metadata management
  • Strong experience with dbt (data build tool) for data modeling, transformation, and orchestration
  • Experience in Data Goverce and Data quality tools like Atlan, Monte Carlo etc.
  • Experience in processing streaming data using Kafka / Pub-Sub
  • Healthcare industry experience
  • Experience in Agile

Skills

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