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Leverage Spark, Airflow, Apache Beam, Google Kubernetes Engine, BigQuery and other tools to build robust and efficient data pipelines. Deep experience with data frameworks and tools like Spark, Spark Streaming, Apache Beam, and Airflow.
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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.
$232,000 - $313,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience with Apache Spark, Databricks. BS, MS, or PhD degree in Computer Science, Data Science, Economics, Statistics, Computational Biology, BioInformatics, or equivalent experience.
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Experience with designing and maintaining data warehouses and/or data lakes with big data technologies such as Spark/Databricks, or distributed databases, like Redshift and Snowflake, and experience with housing,accessing, and transforming data in a variety of relational databases.
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SedonaDB and Apache Spark are built in Java and Scala, with deeply optimized Python wrappers and SDKs, and are deployed on cloud-based Kubernetes environments. Make open-source contributions to Apache Sedona, Apache Spark, and other open-source software packages where necessary.
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Experience building a data platform, with experience in tooling and services such as Airflow, Spark, Flink, Beam, dbt, Dataflow, BigQuery, Tableau, Looker, or equivalent. Engineering Manager, Data Analyticsat Memora Health (View all jobs)Remote - U.S. Based.
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Familiarity with big data processing frameworks such as Apache Airflow or Apache Spark. Astronomer is the driving force behind Apache Airflow, the de facto standard for expressing data flows as code.
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Experience with big data technologies and platforms such as Hadoop, Spark, AWS, CGP, or Snowflake. Work closely with cross-functional teams including marketing, product, and engineering to drive data-driven decision-making and ensure alignment with business objectives.
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Comfortability with data warehouses and big data technologies such as Redshift, Snowflake, Big Query, Presto, Athena, Spark, DBT. The ideal candidate will be adept in navigating the data stack and able to support initiatives in all facets from analytics/data engineering and product analytics to machine learning.
$180,000 - $275,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Data processing technologies and streaming workflows (e.g., Spark, Kafka, Flink, Beam) Data pipeline and workflow orchestration tools (e.g., Airflow, DBT, Luigi, Azkaban, Storm) Tackle novel challenges in blockchain, data science, and threat intelligence.
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Our team leverages cutting-edge open-source technologies such as Apache Spark, Flink, Kafka, Airflow, Delta Lake, and Iceberg to build and maintain a scalable, high-quality data ingestion framework.
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Strong programming skills in languages such as Python, Java, or Scala, with experience in data processing frameworks like Apache Spark or Apache Flink. Data Processing: Architect and implement data processing pipelines using cloud-native data processing frameworks such as Apache Spark, Apache Flink, or Google Dataflow, enabling real-time and batch data processing and analysis.
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Preferred] Experience working with Apache Spark to process large-scale distributed datasets. 4+ years of hands-on industry data science experience, using typical machine learning and data science tools including pandas, scikit-learn, gensim, nltk, and TensorFlow/PyTorch.
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As a Sr Principal Software Engineer within the Identity Engineering organization, you will be responsible for: identifying, or introducing best practices within the organization; setting technical, and architectural direction across the organization; helping squads, and individuals execute on that direction; and providing subject matter expertise to help accelerate project delivery.
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Preferred: 2+ years of experience with a modern data stack (Databricks, Kafka, Spark, Airflow, real-time databases) and cloud data warehouses such as RedShift and Snowflake. Identify, document, and promote data engineering best practices on the team and in the larger organization.
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data engineering apache spark jobs Title: technical writer in San Francisco, Boynton-beach, Florida
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