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Python, Apache Airflow, Apache Spark, PostgreSQL, Presto SQL, Snowflake SQL, Confluence, JIRA Amazon Web Services (Security Groups, Batch, Lambda, S3, ECS, EC2, ALB, RDS, IAM, SNS, Fargate, ElastiCache, Redis.
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Utilize programming languages such as Java, Python, SQL, Node, Go, and Scala, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
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Strong proficiency in Apache Spark, including Spark SQL, Spark Streaming, and Spark MLlib. As a Spark Developer, you will play a key role in designing, developing, and optimizing data processing pipelines using Apache Spark.
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Experience in Snowflake or AKS (Azure Kubernetes Service) for Spark is a plus. x, Apache Spark 3. x, Apache Airflow, Hive, Impala, SQOOP, Informatica, Python, Java.
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Python, Apache Airflow, Apache Spark, PostgreSQL, Presto SQL, Snowflake SQL, Confluence, JIRA. Python, Apache Airflow, Apache Spark, PostgreSQL, Presto SQL, Snowflake SQL, Confluence, JIRA.
Part-timeExpandApply NowActive JobUpdated 19 days ago - UpvoteDownvoteShare Job
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Experience with Hasura , REDIS , Apache Spark , Azure Databricks. This position provides the technical expertise for the complex and intricate client s Azure DevOps and Containerization Tool Stack including but not limited to specializing in the support and administration of the OpenShift Container Platform (OCP) Projects and support for integrations with IIS, Apache Tomcat, JBoss, SQL Server, Windows, Linux, Oracle etc.
Full-timeExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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Experience scaling production systems running Big Data tools like Spark, Hadoop, Apache Druid, Looker. Experience with at least 3 of the technologies/tools mentioned here: HAProxy, Kafka, Big Data/ Hadoop, Presto, Spark, Airflow, Pinot, Druid, Opensearch, Gcp, Data Proc.
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Experience implementing automated workflow, such as using dbt for BigQuery transformations, orchestrated by Apache Airflow and/or Kubernetes, with industry standard CI/CD tools. Hands-on experience with modern big-data technologies such as Apache Spark or Presto.
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Apache Spark, Kubernetes, Kafka, SIMP Project, Ansible, Docker, GIT, Red Hat Enterprise Linux (RHEL), Suricata, Zeek, Kibana, Logstash, Elastic Search, Neo4J, PostgreSQL, AWS Cloud & Nifi.
$100,000 - $125,000 a yearFull-timeExpandApply NowActive JobUpdated 3 months ago - UpvoteDownvoteShare Job
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Amazon Web Services (Security Groups, Batch, Lambda, S3, ECS, EC2, ALB, RDS, IAM, SNS, Fargate, ElastiCache, Redis) At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud.
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4+ years using modern platforms & technologies, such as big data, data warehouses, data lakes, and data lakehouses; proficiency with Elixir; proficiency with Snowflake; familiarity with Databricks. Anglepoint’s software engineering department based in Lindon, UT seeks a dynamic, highly skilled & experienced Principal Data Architect to revolutionize our data landscape within a new enterprise-scale, cloud-native, microservices-driven platform, providing data processing, abstraction, and reporting that empower our service delivery and internal business units to achieve next-level productivity and client value.
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Develop, program, and maintain applications using the Apache Spark open-source framework. Must be strong in Cloud AWS event-based architecture, Kubernetes, ELK (Elasticsearch, Logstash & Kibana.
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Demonstrate expertise and hands-on experience with Apache Spark tools such as Google Dataproc, Amazon EMR, and Databricks. 8+ years experience demonstrating an established track record in Data Engineering and Machine Learning; experience with GPUs as well as expertise in tuning and analyzing Apache Spark workloads.
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At least 6 years of experience in software engineering (Internship experience does not apply) Lead a portfolio of diverse technology projects and a team of developers with deep experience in full stack systems to create automation tools to support the Card Architecture team aligned with leading standards and practices including tooling solutions for Content Management, SDLC, DevOps, reporting, etc.
Part-timeExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
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We use Apache Airflow, Python, and Apache Spark for ETL. For streaming data, we use Apache Kafka managed by a vendor and use Kafka Connect, Kafka Streams, and Spark Streaming for stream processing.
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