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Comfortability with data warehouses and big data technologies such as Redshift, Snowflake, Big Query, Presto, Athena, Spark, DBT. Remote Data Scientist. 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.
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Experience with GCP products such as BigTable, BigQuery, Dataproc, PubSub or other data tools like Kafka, Hive, or Apache Beam. Project categories: besides product requests and enhancements, we work on projects in performance and cost optimization, security and legal compliance, reliability and quality initiatives, as well as architectural refreshes such as POC in restructuring our data to be more streaming/real time friendly, new REST API for relevant services, migration of apps to Spark, Parquet, and other new technologies that could make our processing faster, more scalable, maintainable and cost effective.
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Hands-on experience with big data technologies, including Apache Spark and Databricks Delta Lake. Stay abreast of the latest advancements in Databricks and other relevant technologies to continually enhance data engineering practices.
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Work with AWS big data technologies including EMR, Glue, S3, EKS, Lambda, Athena, RDS. 6+ years’ experience working within the AWS Big Data/Hadoop Ecosystem (EMR, Glue and Athena.
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Utilize Databricks for big data processing, analytics, and machine learning workflows. Architect, implement, and maintain scalable data architectures to meet our client's data processing and analytics requirements.
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Experience with big data and workflow management technologies like Hadoop, Spark, Redshift, Athena, Airflow, etc. Data platform: Hadoop, Hbase, OpenSearch, Kafka, Spark, Flink, Go, Java, SQL, Databricks, Snowflake, BigQuery.
$145,000 - $190,000 a yearExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Partner closely across the business to find improvements/opportunities and influence decisions using data science methodologies and tools. Industry experience with proven ability to apply scientific methods to solve real-world problems on large scale data.
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Experience with dbt or similar analytics workflow tools a big plus. 4+ years of professional experience as a data scientist in the SaaS industry. We are a top-notch data organization with a great culture and have the same high standards with our code, systems, practices, and people.
$152,000 - $170,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience working with cloud or on-prem Big Data/MPP analytics platform (i.e. SnowFlake,Netezza, Teradata, AWS Redshift, Google BigQuery, Azure Data Warehouse, or similar). 3+ years' of experience with workflow management engines (i.e. Airflow, Luigi, Prefect, Dagster, digdag.io, Google Cloud Composer, AWS Step Functions, Azure Data Factory, UC4, Control-M.
$94,500 - $122,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Implement the data analysis pipelines using standard Big Data technologies (Spark, Airflow) Opportunity to expand your knowledge of data engineering tools and platforms using state-of-the-art tech stack.
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Working with at least one cloud based data warehousing platforms – Snowflake, AWS Redshift, Azure DW, Oracle Cloud, Google Big Query, or anything similar. The Data Operations Manager will also work closely with Engineering, Analytics and Product Management teams, in providing actionable insights and support for strategic initiatives along with building powerful tools for taxonomy administration.
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Experience leveraging big data technologies (Hive/Hadoop) and modern data visualization tools (Tableau, ThoughtSpot, Looker) to blend data from multiple sources to help answer multi-dimensional business questions.
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Experience with data-intensive applications, big data pipelines and analytics, having used tools such as Snowflake, DataBricks, Amplitude and Looker. Develop and support cloud-based big data pipelines.
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Guide engineering teams in the design and development of commerce applications, with specific emphasis on Shopify, Sales Force Commerce Cloud, and Big Commerce. Over the last decade, Trove has equipped leading brands with technology and operations to create and scale branded resale programs by enabling customer trade-in of items, single-SKU identification and condition grading, site build and maintenance, and customer data collection, analytics and reporting.
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4+ years experience in engineering data pipelines using big data technologies (Python, pySpark, Real-time data platform like Active MQ or Kafka or Kinesis) on large scale data sets.
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big data jobs Title: big data architect Company: Wells Fargo in San Francisco, CA
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