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Significant experience in software engineering and data engineering roles, with a focus on snowflake and Databricks. Design, construct, install, test and maintain highly scalable data management systems, specifically focusing on Snowflake and databricks platforms.
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Design new software and Data Engineering applications in the Snowflake Environment. You will be driven to learn about FreeWheel's Ad-Tech driven products (MRM, Beeswax, Strata, and others) and how their processes are implemented in Snowflake and other Tools such as Tableau, Looker, and You will be a subject matter expert that understands how data flows across our platforms and assist in creating cleaner and streamlined data workflows throughout the FreeWheel Enterprise.
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You will be driven to learn about FreeWheel s Ad-Tech driven products (MRM, Beeswax, Strata, and others) and how their processes are implemented in Snowflake and other Tools such as Tableau, Looker, and SalesForce.com. You will be a subject matter expert that understands how data flows across our platforms and assist in creating cleaner and streamlined data workflows throughout the FreeWheel Enterprise.
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As a Snowflake Data Governance Steward/Eng. 3 on FreeWheel's Trust and Standards Tools & Insights team, you will leverage a dynamic skill set in our rapidly growing Snowflake Environment.
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Reporting directly to the Director, Business Applications, this position will be responsible for leading data strategy, contributing to enterprise data lake & analytics platforms using Snowflake, Fivetran and DBT technologies and drive standardization, operational excellence across the organization.
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Author and review Data Governance and Snowflake standards and best practices in written form. Conduct regular presentations both in person and remotely to all levels of the FreeWheel organization on Data Governance and Snowflake best practices.
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Assist Trust and Standards Management in development of standards, guidelines, and best practices for Snowflake and general Data Governance at FreeWheel. You will have a passion for Data Governance and Data technologies and will code, test, and debug new and existing applications using SQL and other Data Engineering and BI Tools.
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You will be utilizing Snowflake and/or Databricks tools, cutting-edge DevOps technologies, developing advanced analytics products, and applying data and statistical programming tools to enterprise data to advance and enable key mission outcomes within cloud environments (GCP, AWS, Azure.
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Knowledge of Hyperscale SQL Server and Snowflake Data engineering best practices around data modelling, evaluation, deployment, and governance. 3+ years of Snowflake development experience in Data Engineering and architecting, building, and demonstrating data solutions.
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8+ years data engineering experience focused on Snowflake, Databricks, Kafka, AWS Glue, Airflow, and AWS services. Design and build data pipelines: Design, develop, and implement data pipelines using Kafka, Airflow, AWS Glue, Python, and Lambda functions to ingest, transform, and load data into Snowflake.
$130,000 - $160,000 a yearFull-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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You will have a technical and business understanding and thought leadership on approaches to industry leading deployments of Data Lakes, Data Warehouses, Data Marts, and the progression of data from raw/bronze to curated/gold environments with an interest in all tools/technologies including Python, Matillion, Snowflake, Databricks and Azure.
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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.
ExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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The Director, Data & ML Engineering willl be responsible for both data engineering and MLOps engineering teams to support data science applications. Oversee the entire lifecycle of data engineering projects: build scalable, reliable, and high performing data ingestion pipelines that collect, transform, integrate, and load structured, semi-structured, and unstructured data from a variety of sources, such as transactional data, data warehouse, and data lakes.
Full-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Must have multiple examples of managing large, enterprise-level data and ML engineering projects. Extensive experience using Snowflake, AWS SageMaker, GCP/GCP BigQuery, DBT, and Airflow for AI/ML model deployment and operationalization.
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Have hands-on experience developing and supporting a modern data infrastructure, including cloud data warehouses such as Snowflake, BI tools such as Looker, and data orchestration platforms such as Airflow.
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