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Responsibilities: • Deep understanding of Google Cloud Platform's data services, including BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Storage. • Proficiency in designing and implementing data pipelines, data warehousing solutions, and ETL processes within GCP. • Experience with stream and batch data processing architectures and technologies. • Strong programming skills in Python, Java, or Scala, with a focus on data engineering tasks. • Knowledge of SQL and experience with big data querying tools. • Familiarity with data modeling, data governance, and data security best practices. • Experience with machine learning tools and services on GCP is a plus. • Understanding of DevOps practices for data engineering, including CI/CD pipelines for data pipelines and infrastructure as code. Educational Requirements Master Of Comp. Applications,Master Of Science,Master Of Technology,Bachelor Of Comp. Applications,Bachelor Of Commerce,Bachelor Of Science,Bachelor Of Technology,Bachelor of Engineering Additional Responsibities: None Technical and Professional Requirements: • Lead the design and implementation of scalable and reliable data pipelines and data processing solutions on GCP. • Manage and mentor a team of data engineers, fostering a culture of continuous improvement and innovation. • Collaborate with data scientists, analysts, and business stakeholders to understand data needs and deliver comprehensive data solutions. • Ensure data quality, data governance, and data security standards are met across all data engineering initiatives. • Optimize data processing architectures for performance and cost efficiency. • Stay abreast of the latest GCP features and data engineering trends, incorporating best practices and technologies into our data solutions. • Lead the development of data models and data warehousing solutions that support analytics and business intelligence activities. • Oversee the deployment and operation of data pipelines, monitoring their performance and troubleshooting issues as needed.
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