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Familiarity with data warehousing concepts and schema design principles (e.g., Star Schema, Snowflake Schema) Experience with big data technologies such as Snowflake, Hadoop, Spark, Airflow, or Flink.
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The primary objective of the Data Organization is to harness healthcare data to support and promote value-based care contracts between health systems, providers, health plans, and other third-party risk bearing entities; incentivize quality, utilization, and experience outcomes; and enhance payment operations with both services and product development.
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The Cyber Security Specialist (Data Security) continuously identifies, tracks, shares, and supports operational IT security requirements across the Ninth Circuit, with an emphasis on data security and analysis.
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Experience with Customer Data Platforms (CDP) like Segment, mParticle, Tealium AudienceStream or other industry leading CDP technology would be a plusHands-on experience with marketing platforms such as Google Analytics, Adobe Analytics, Marketo, HubSpot, Salesforce Marketing Cloud, etc would be a plusFamiliarity with cloud platforms such as AWS, Azure, or Google Cloud, and their data services (S3, Redshift, BigQuery, etc.
ExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Advanced experience in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc. What you’ll be responsible for:As a member of the Data Engineering - Business ETL team, you own the ETL/ELT pipelines and data warehouse that is used for financial and regulatory reporting.
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Collaborate with technical teams to leverage technology solutions for knowledge management within data center construction projects, including document management systems, collaboration platforms, and data analytics tools.
ExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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Strong technology proficiency in one or more of the following areas is highly desired: Aladdin technology suite, data model & data feed interaction, API’s, industry technology (e.g. CNS, Swift, OMGEO), data and reporting toolsets (e.g. ADS/SQL, Microsoft Excel VBA/Macros, Power BI), Python, etc.
ExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Experience with data visualization tools such as Tableau, MixPanel, Google Looker. The Lead Data Scientist will formulate Glo’s data strategy and work with the Data Engineer to implement the appropriate architecture and execute on the strategy.
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CI/CD orchestration (Jenkins, CircleCI, or TravisCI)ETL, data modeling, cloud-based data storage, processingGCP Data Services (Dataflow, BigQuery, Dataproc)Workflow and data pipeline orchestration (Airflow, Oozie, Jenkins, etc)Container orchestration technologies (Kubernetes, OpenStack, Docker swarm, etc)Open source software involvementMonitoring/Logging with technologies like Splunk, ElasticSearch, Logstash/Fluentd, Stackdriver, Time-series databases like InfluxDB etc.
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Expert skills in SQL, Excel, and Tableau data visualization tools. BS in Computer Science, Engineering, Statistics, Mathematics, or a related quantitative field and 4+ yrs of experience as a Marketing/Product Analyst, Data Analyst, Data Scientist, BI Engineer, Analytics Engineer, or similar role.
$144,000 - $180,000 a yearFull-timeExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
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Experience with relational databases and building modern data pipelines Hands-on experience working with cloud technologies (OCI, AWS, Azure, GCP) Familiarity with Big Data components like Apache Spark, Apache Hudi, etc.
$96,800 - $251,600ExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Our primary developer offering is an ultra-performant Data Processing Framework (unified streaming + batch) with a Python API, distributed Rust engine, and capabilities for data source integration & transformation at scale (Kafka, S3, databases/CDC.
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The Senior Analytics Engineer is responsible for integrating data into the Enterprise Data Warehouse (EDW) from various internal and SaaS sources using a cloud ELT platform, AWS Lambda/Glue, and Python to support downstream teams with reporting (Snowflake, Databricks or Redshift.
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Experience working with large-scale, end-to-end data platforms and analysis solutions with exposure to platforms and tools such as [Databricks, Spark, Kafka, Cassandra, MongoDB, Redis, MySQL, DBT, Tableau, and Mode] preferred.
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As the lead data scientist on these teams, you will leverage data insights to identify opportunities, inform key product and business investment decisions, and play a critical role in helping Jerry become the first, truly connected ecosystem for car owners.
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