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Responsible for day-to-day Onshore - Offshore service delivery operations for Big Data, Cloud, Middleware Integration, SNOWFLAKE, Databricks applications. Experience with Customer support service delivery for Integration Big Data, Cloud, Middleware Integration, SNOWFLAKE, Databricks technology environments.
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Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and (GCP, AWS, Azure, Snowflake) ‘big data’ technologies.
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Experience with modern data platforms (Azure Synapse, Databricks, Redshift, Big Query, Snowflake). Technical Integration: Develop and implement technical requirements into our data workflows, collaborating closely with your manager and senior engineers.
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5+ years in designing, solutioning the Snowflake, Databricks and Big data tools including DataOps, Data engineering, Data Integration, Data Orchestration and Data Marketplace.
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Big Data Expertise : 3+ years of hands-on experience with major Big Data technologies and frameworks, including Spark, Hive, ZooKeeper, HDFS, Presto, Hadoop, MapReduce, Tensorflow, and more.
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Experience working with cloud or on-prem Big Data/MPP analytics platform (i.e. SnowFlake,Netezza, Teradata, AWS Redshift, Google BigQuery, Azure Data Warehouse, or similar). 3+ years' of experience with workflow management engines (i.e. Airflow, Luigi, Prefect, Dagster, digdag.io, Google Cloud Composer, AWS Step Functions, Azure Data Factory, UC4, Control-M.
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This role requires a deep understanding of big data technologies, particularly Apache Spark, as well as expertise in data engineering and analytics. Proven experience as a Technical Lead with a focus on Databricks and big data technologies.
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Driving Results: Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Python and/or Node.js, SQL (using dbt for transformation), commercial SaaS and OSS offerings, and AWS ‘big data’ technologies.
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Experience with Big Data Technologies (NoSQL databases, Hadoop, Spark, Elasticsearch, Databricks, etc.) Experience in architecting data pipelines and solutions for streaming and batch integrations using tools/frameworks like dbt, Talend, Azure Data Factory, Spark, Spark Streaming, etc.
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As a Sr. Big Data Engineer, you will work with a variety of talented teammates and be a driving force in technical initiatives that will accelerate analytics at Client. Big Data Engineer.
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We’re looking to expand our Big Data Engineering team to keep pace. 5+ years’ experience in large-scale software development/Big Data technologies. Client is embracing Big Data technologies to enable data-driven decisions.
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Design and implement distributed data processing pipelines using Spark, Hive, Python, Airflow, and other tools and languages prevalent in the Hadoop ecosystem. You will be working on projects that build data artifacts to answer questions about consumer behavior, commerce trends, consumer touchpoint preferences and more.
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Take part in DevOps by building utilities, user defined functions and frameworks to better enable data flow patterns. You will collaborate with Product managers, Data Scientists, Engineering folks to accomplish your tasks.
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Expert knowledge and experience in Databricks, Lake House, Structured Streaming, Kafka, Delta Lake, Delta Live table, Delta shareetc. Explore and build proof of concepts using open source NOSQL technologies such as HBase, DynamoDB, Cassandra and Distributed Stream Processing frameworks like Apache Spark, Kafka stream.
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As the Manager of Data Engineering, you'll lead exciting technical projects and manage budgets from start to finish, while transforming our internal engineering teams into efficient, scalable, and reliable forces.
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big data jobs Title: data manager Company: Geico
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