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Understanding of relational databases (e.g., Snowflake, Google Big Query, Databricks, Redshift, Synapse), data warehousing, ETL, web services, SaaS technologies, etc. Experience with data modeling, data warehousing, data engineering, data integration.
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These technologies include but are not limited to: Microsoft, SAP, Qlik, Snowflake, Alteryx, Automation Anywhere, and Workday Adaptive Insights. Your proficiency in data modeling, database design, and data warehousing will serve as the bedrock for pioneering innovations, coupled with hands-on experience across various data sources and platforms, with a specific emphasis on Microsoft Azure.
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The ideal candidate will have extensive experience with AWS Glue, Spark, Python, and Snowflake, with a strong background in data engineering, ETL processes, and data warehousing. Work closely with data architects and analysts to design and implement data models, schemas, and structures in Snowflake, with a focus on data governance principles such as data lineage, data quality monitoring, and metadata management.
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Nice to have: High-level understanding of distributed computing, database cluster fundamentals (such as Apache Spark, Snowflake, etc) We are committed to growing a diverse and welcoming team in a safe space to be yourself and learn from the most innovative minds in blockchain and data warehousing.
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Knowledge of data warehousing, Snowflake, SQL, Databricks. Knowledge of common databases like SQL, Databricks, advanced excel, VBA, advanced PowerPoint, Engagement and execution data, etc.
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Experience managing production data pipelines or warehousing data (e.g., Modern Data Warehouse stacks such as dbt, Airflow, Looker, Cloud Composer, BigQuery, Snowflake). Work with analysts and engineers to help shape and drive the development and application of Google’s internal data infrastructure including warehousing, reporting, and analytics platforms.
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Data Warehousing, Data modeling, Data mastering, Data quality, ETL, Informatica, Alteryx, MSSQL, Oracle, Teradata, Hadoop, Snowflake, MSSQL, SSIS, SSRS, PowerBI, Tableau, Python, R, Scala, SPARK a další programovací jazyky, reporting, ETL nebo další datové nástroje.
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Experience with SQL, Python, Data Warehousing, DBT, Airflow and Kafka. You will be working on infrastructure that is already set-up and continuously improving with technologies such as: AWS, Singer, Snowflake, Airflow, DBT, and Metabase, and with them we invite you to change the vicious cycle of problems in healthcare.
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Expertise working with enterprise data warehousing solutions, like Databricks, Snowflake, and BigQuery. Expertise working with enterprise data warehousing solutions, like Databricks, Snowflake, and BigQuery.
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Requirements: Expertise in SQL and relational schema design, strong Python scripting skills, familiarity with cloud environment, familiarity with Databricks, familiarity with orchestration tools like Apache Airflow, proficiency in spoken and written English Responsibilities: Designing, developing, and maintaining data processing systems with a focus on Data Warehousing.
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Proven experience working as a Data Engineer with a focus on ETL processes, data integration, and data warehousing. TITLE: Data Engineer - AWS Glue, Spark, Python, Snowflake. Strongly preferred experience with Spark and Snowflake.
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The ideal candidate will possess deep technical expertise in Python programming, Snowflake data warehousing, AWS cloud services, Kubernetes (EKS), CI/CD methodologies, Apache Airflow, dbt, Kafka for real-time data streaming, and API development.
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Hands-on experience in working with different types of databases; large relational storage engines (MySql and AWS RDS) and distributed storage engines (HDFS/Hadoop, NoSQL and Cloud tools such as S3, Redshift, Snowflake.
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The candidate must have a strong understanding of enterprise data practices, data engineering, data modeling techniques and experience with industry adopted analytics applications and data platforms (Snowflake, SAP HANA, ELT/ ETL Tools, Orchestration Tools, SSIS.
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Experience with cloud-based data platforms and data warehousing solutions (e.g., Snowflake, Redshift, BigQuery). Partner with the data engineering team to design and maintain scalable data pipelines, ETL processes, and data warehousing solutions.
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snowflake warehousing jobs in Snowflake, AZ
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