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Database / Warehouse: PostgreSQL, DynamoDB, Databricks Unity Catalog. Experience with AWS + Databricks Unity Catalog / Model serving. Distributed Compute: Spark/Databricks. Frameworks: Flask, React, Tailwind, REST.
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Proficient in data engineering roles with a focus on AWS and Databricks. Utilize Databricks for big data processing, analytics, and machine learning workflows. Optimize data processing and query performance for large-scale datasets within AWS and Databricks environments.
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Experience deploying and maintaining pipelines (AWS, Docker, Airflow) and in engineering big-data solutions using technologies like Databricks, S3, and Spark. Experience engineering big-data solutions using technologies like EMR, S3, Spark, Databricks.
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Familiarity with data exploration and data visualization tools like Tableau, Looker, etc. Flexible work from home options available. Familiar with metadata management, data lineage, and principles of data governance.
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G., Databricks, Snowflake, and DBT) are advantageous. Data Engineering: Develop & Lead the development Efforts in building data pipelines using PySpark, Databricks, and Snowflake. - Significant experience in implementing PySpark, Databricks, and Snowflake.
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Skill set centered around Databricks, including proficiency in SQL for complex query writing, a deep understanding of Databricks' collaborative notebooks for applying business logic and conducting data analysis, expertise in Apache Spark for leveraging big data best practices, and familiarity with data integration techniques to connect Databricks with visualization tools like PowerBi or Graphana.
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Design and maintenance of pipelines built atop distributed data technologies (Databricks/Spark, Snowflake, BigQuery/Redshift, Kafka/Kinesis, etc.) You'll build out our data platform capabilities across a wide selection of themes (pipelines, graphs, ml models, annotations, automation, data observability, data lifecycle management, data governance, semantic layers) using a set of core services (currently AWS, Databricks, and Looker.
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Oversee the implementation of Spring Boot, Angular/React JS, Kafka, NoSQL databases, open-source RDMS, Databricks, Kubernetes, Familiarity with the specified technology stacks - Spring Boot, Angular/React JS, Kafka, NoSQL databases, open-source RDMS, Databricks, Azure or any other cloud Platform.
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For accelerating and driving innovative solutions at scale, Indium has developed strong intellectual properties such as teX.ai, which automates the text analytics lifecycle by leveraging ML, NLP, and Gen AI; ibriX, a pre-built accelerator for Databricks implementation lifecycle; uphoriX, a smart test automation platform; iDAF, an accelerator for end-to-end Data validation.
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AWS Cloud, AWS services (Redshift, RDS, S3, Glue ETL, Glue Data Catalog, EMR, PySpark, Python, Lake formation), (DevOps OR Jenkins or any CI/CD), Databricks, Starburst. Experience with building data analytical platform using Databricks (data pipelines), Starburst (semantic layer) on AWS cloud environment.
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Tech stack includes Airflow, Spark, Databricks, Delta Lake, and Snowflake. Experience with at least one major Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Databricks, Big Query.
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Hands-on production environment experience with distributed processing systems such as Spark Hands-on production experience with data pipeline orchestration systems such as Airflow for creating and maintaining data pipelines.
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Demonstrated experience using data processing tools, such as Airflow, Spark, dbt, Fivetran, Databricks, Talend. Demonstrated experience using data processing tools, such as Airflow, Spark, dbt, Fivetran, Databricks, Talend.
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Deep expertise in Databricks, Apache Spark, including Delta Lake, and proficiency in Spark SQL. Implement state-of-the-art Featurestore within Azure Databricks or AzureML, adhering to industry-leading practices in data management and scalability.
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Nice to have: Databricks, Snowflake, Teradata, Oracle, Google BigQuery, Hadoop and related stack. Nice to have: Databricks, Snowflake, Teradata, Oracle, Google BigQuery, Hadoop and related stack.
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databricks job in Los Angeles, CA
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