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Azure Data Engineer (Lead) with skills Oracle ADF, Azure Data Factory, synapse, databricks, Azure Datalake for location Bangalore, India Experience in building ETL / data warehouse transformation processes Direct experience of building data pipelines using Azure Data Factory and Apache Spark (preferably Databricks.
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You will be utilizing Snowflake and/or Databricks tools, cutting-edge DevOps technologies, developing advanced analytics products, and applying data and statistical programming tools to enterprise data to advance and enable key mission outcomes within cloud environments (GCP, AWS, Azure.
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6-8 years of strong experience in Spark, Python, Shell Scripting, PostgreSQL, Hadoop, AWS (S3, EC2, SNS, SQS, Lambda, ECS, Glue, IAM, and CloudWatch), Databricks (Delta lake, Notebooks, Pipelines, cluster management, Azure/AWS integration.
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What you will likely bring:Strong experience in Microsoft Azure Proficiency in data processing frameworks such as Azure Spark, or cloud-native data processing services (Azure Data Lake, Azure Data Factory, Azure Databricks, Azure Synapse, Snowflake, CosmosDB) Experience with data integration and ETL (Extract, Transform, Load) processes, including tools like cloud-native orchestration services.
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Data warehouses and file stores such as Snowflake, RedShift, Teradata, BigQuery, Amazon S3, Amazon RDS, Azure Synapse, Databricks Lakehouse, etc. Data warehouses and file stores such as Snowflake, RedShift, Teradata, BigQuery, Amazon S3, Amazon RDS, Azure Synapse, Databricks Lakehouse, etc.
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Software Development: Collaborate with cross-functional teams to design, implement, and maintain software solutions using various programming languages and technologies, including C#, ASP.NET, React, SQL Server, Postgres, Databricks, Python, Terraform, and Elasticsearch.
$115,000 - $180,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Proficiency in data processing frameworks such as Azure Spark, or cloud-native data processing services (Azure Data Lake, Azure Data Factory, Azure Databricks, Azure Synapse, Snowflake, CosmosDB.
ExpandApply NowActive JobUpdated 14 days ago - UpvoteDownvoteShare Job
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Experience with Azure cloud services, Databricks, Apache Spark, Delta Live Table, ML Flow, Unity Catalog. As a Data Engineer in Everi Games division, you will be building scalable and highly optimized data infrastructures and pipelines using Azure and Databricks.
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Collaborating amongst team members across several geographies, our Cloud practitioners engineer cloud-based analytics solutions on AWS, Azure, Databricks, GCP, Snowflake, Oracle, Informatica Cloud and a combination of native cloud technologies, including computing at edge and curating data-in-motion.
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Big Data Tools: Kubernetes (K8s), Hadoop, Spark, Postgres, Databricks, Azure cloud offerings including (Azure Synapse, ADLS, Azure Functions) Expert on Databricks platform - DLT Streaming Pipelines, Workflows, Notebooks, DeltaLake, Unity Catalog, Dashboards.
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Experience working with large datasets and cloud-based enterprise data warehouse solutions (e.g., Microsoft Azure, Databricks, Snowflake) preferred. Experience working with large datasets and cloud-based enterprise data warehouse solutions (e.g., Microsoft Azure, Databricks, Snowflake) preferred.
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Experience using Big Data or Cloud integration technologies such as Databricks, Matillion, Azure Data Factory, AWS Glue, AWS Lambda, etc. Hands-on technical experience with DevOps and CI/CD processes and tools, such as Azure DevOps, Jenkins, AWS CodePipeline, and Google Cloud Build.
Full-timeExpandApply NowActive JobUpdated 25 days ago - UpvoteDownvoteShare Job
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SKILLS: Background in working with Azure Cloud Services: Data Factory, SQL database, Functions, Data Lake, Databricks, Logic Apps, and Azure Automation. RESPONSIBILITIES: Design data pipelines to extract data from different data sources using Azure, Snowflake Cloud, and cloud-native technologies.
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Proficient in Microsoft data and analytics technologies including Azure Synapse, Azure Data Factory and Azure Databricks. Experience with big data technologies that may include the following: Azure Cosmos DB, Kubernetes Services, Azure ML, NoSQL, MongoDB, Cassandra, Couchbase, etc.
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Collaborating amongst team members across several geographies, our Cloud practitioners engineer cloud-based analytics solutions on AWS, Azure, Databricks, Google Cloud Platform, Snowflake, Oracle, Informatica Cloud and a combination of native cloud technologies, including computing at edge and curating data-in-motion.
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