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Hands on experience of building data pipelines using Apache Spark (Azure Databricks), Scala. Job profile : Data Engineer experience on Spark with Scala / Azure Databricks. Minimum 3-4 years of experience on Spark with Scala / Azure Databricks.
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Python, SQL, Spark, Kafka, Snowflake, Golang, Scala. Moden data engineering tooling and systems – Spark Databricks, Snowflake, Airflow, Kafka. Indepth data engineering experience – Python, Scala, Golang, SQL.
ExpandApply NowActive JobUpdated 13 days ago - UpvoteDownvoteShare Job
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<> Tech Skills - Scala, Spark, GCP, Dataproc, Hadoop, Airflow, SBT, Maven, Docker, Kubernetes, pyspark, Jenkins, Bigquery <> Experience with workflow management tools such as Jenkins, Airflow.
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Your expertise in ETL, Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks will be essential in ensuring efficient data processing and analysis. High level of proficiency in ETL processes and demonstrated, hands-on experience with technologies such as Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks.
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Writing Scala code with tools like Apache Spark + Apache Arrow + Apache Kafka to build a hosted, multi-cluster data warehouse for Web3. As a Data Engineer for our Data Platform Engineering team you will join skilled Scala/ Spark engineers and core database developers responsible for developing hosted cloud analytics infrastructure (Apache Spark-based), distributed SQL processing.
Full-timeExpandApply NowActive JobUpdated 3 months ago - UpvoteDownvoteShare Job
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Tech stack: Google cloud, HDFS, SPARK, Scala, Python (optional), Automic/Airflow, BigQuery, Kafka, API, Druid. Expertise in big data technologies like Hadoop, Apache Spark (Scala preferred), Apache Hive, or similar frameworks on the cloud (GCP preferred, AWS, Azure etc.
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Design, develop, and implement end-to-end data pipelines, utilizing ETL processes and technologies such as Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks. Knowledge of Qlik/Qlik Sense, QVD/QlikView, and Qlik Production Application Standards (QPAS) is a significant plus.
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Knowledge of Qlik/ Qlik Sense, QVD/ QlikView, and Qlik Production Application Standards (QPAS) is a huge plus. Understanding of data modeling/ visualization, database design principles, and data governance practices.
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BigBear.ai's customers, which include the US Intelligence Community, Department of Defense, the US Federal Government, as well as customers in manufacturing, healthcare, commercial space, and other sectors, rely on BigBear.ai's solutions to see and shape their world through reliable, predictive insights and goal-oriented advice.
Full-timeRemoteExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Getting your hands-on modern technologies and big data tools, including Hadoop, Kafka, Cassandra, MongoDB, Hive, HBase, Impala, Sqoop, Flume, Oozie, Zookeeper, Pig, Cloud Computing, Spark, Scala.
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BigData, Scala, Hadoop, AWS EMR, AWS EC2, AWS Airflow, Snowflake, AWS Athena, Spark, Python, PL/SQL, Tableau, Angular, CI/CD. You should be comfortable working in a fast-paced environment and can help build APIs, Calculators, on new cutting edge cloud and big data technologies such as AWS EMR, EC2, Scala Spark, Scala, Snowflake.
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Programming Language: Python, R, SQL, Java, Scala, Pyspark/Apache Spark, Shell scripting. Use programming languages including but not limited to Python, R, SQL, Java, Scala, Pyspark/Apache Spark, Shell scripting.
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Data: PostgreSQL, Firestore, BigQuery, Elastic Search, Prefect, Kafka, Scala, Spark, dbt. Experience with Scala and Spark or PySpark. Modern ETL tools (Apache Beam, Kafka, Spark or similar.
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As a Sr. Software Engineer for our Data Platform Engineering team you will join skilled Scala engineers and core database developers responsible for developing hosted cloud analytics infrastructure (Apache Spark-based), distributed SQL processing frameworks, proprietary data science platforms, and core database optimization.
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Writing Scala code with tools like Apache Spark + Apache Arrow to build a hosted, multi-cluster data warehouse for Web3. 3+ years experience with Scala and Apache Spark. 6+ years experience engineering software and data platforms / enterprise-scale data warehouses, preferably with knowledge of open source Apache stack (especially Apache Spark, Apache Arrow, and others.
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