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Additional Technologies: Spark, Databricks, Kafka, Kinesis, Hadoop, Lambda, EMR. Database: SQL Server, PostgreSQL,Snowflake,Redshift, Aurora,Presto,BigQuery,Oracle. PopularCertifications: AWS Cloud Practitioner,Microsoft Azure Data Fundamentals, Google Associate Cloud Engineer.
ExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
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Must be familiar with big data technologies like Hadoop, Spark, Hive, Databricks. Must be familiar with big data technologies like Hadoop, Spark, Hive, Databricks. Implement automation and orchestration using Azure DevOps, or other relevant tools to streamline deployment and management processes.
ExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark, Delta Lake and MLflow.
RemoteExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Responsibilities: Leveraging the Scrum methodology to plan and execute tasks within the project Program Increment strategy Software development includes use of Python, Java and various shell scripting activities Software architectures and Frameworks include use of Apache NiFi, Databricks, Spark, Hadoop, HUDI technologies Cloud infrastructure is deployed using AWS C2S available services in the IDL VPC boundaries.
ExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Experience with data engineering tools like Databricks, DBT, Fivetran, etc. Experience with big data technologies such as Hadoop, Spark, or Hive. Experience with data engineering tools like Databricks, DBT, Fivetran, etc.
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Experience maintaining, troubleshooting, and configuring Big Data Processing and cloud based platforms: ETL, Hadoop, Elasticsearch for Hadoop, structured data, SQL schemas and queries, Databricks, etc.
Full-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Fringe -A company paid stipend program for personalized lifestyle benefits, allowing employees to choose benefits that matter most to them - ranging from vendors like Netflix, Spotify, and GrubHub to services like student loan repayment, travel, fitness, and more.
Full-timeExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
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X; 2 years of professional experience using big data technologies including Spark, Databricks EMR, Snowflake, Hive, Hudi, Delta, or Hadoop; and 2 years of professional experience writing ETL data workflows.
ExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Minimum 6 years of experience in creating robust enterprise-grade data engineering pipelines using SQL, Python, Apache Spark, ETL, ELT, Databricks Technology Stack, Azure Cloud Services, Cloud-based Data and Analytics platforms required.
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Hands on experience with Databricks. Databricks certification preferred. 8+ years of experience in Hadoop, MapReduce, HDFS, Spark, Streaming, Kafka and NoSQL. Hands on experience with Databricks.
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Tech skillsAdvanced knowledge of Databricks architectureExperience working with various cloud providers (AWS, GCP, Azure)Previous use of Databricks in their most recent roleExperience working in a start up environmentKnowledge of big data technologies (Hadoop, Pyspark.
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Knowledge of Cloud computing / SaaS / IaaS / PaaS technologies - Microsoft Azure, databricks. Knowledge of Big Data Analytics - HAVeN / HADOOP/ Autonomy / Vertica. Knowledge of Cloud computing / SaaS / IaaS / PaaS technologies - Microsoft Azure, databricks.
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Should be an expert in ETL/Pipeline Development using tools such as Azure Databricks and Azure Data Factory with development expertise on batch and real-time data integration. Hands-on experience on major components of the Hadoop ecosystem such as Spark, HDFS, Hive, Sqoop, Kafka, and Streaming is a must.
Full-timeExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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Experience in spark / python (PySpark) / Azure products like Synapse, ADF, Databricks / Autosys. Minimum 7+ Yrs of experience required- Experience in structured databases( Oracle, MSSQL) and unstructured databases (Hadoop.
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Databricks experience is a nice to have. 2+ years of experience in some of the Big Data technologies: Hadoop (HDFS, Hive, Impala) or Kafka or Spark. Hadoop, HDFS, Kafka, Spark, Datalake.
ExpandApply NowActive JobUpdated 6 days ago
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