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3+ years’ experience with a cloud data lake/warehouse solution (SQL Server, Snowflake, Databricks, Azure Data Warehouse, etc. Experience with Azure data integration and orchestration tools, such as Data Factory, Databricks, or Synapse Analytics, for building end-to-end data pipelines or similar tools and technologies.
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1 or more years of experience working with non-rdbms data warehouse/lake stores (such as Big Query, Snowflake, Databricks Delta Lake, or Redshift) You’ll work to ingest and process both streaming and batch data using leading-edge cloud tools from AWS and Databricks that represent purpose-built architecture.
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Experience using industry-standard data visualization tools such as Tableau, Power BI, R or similar platforms. Previous teaching experience at the undergraduate or graduate level, or relevant professional experience in data visualization.
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Maintain and implement improvements to existing data science solutions. Responsibilities include but not limited to: Perform basic data analysis/science tasks such as: data wrangling, exploratory data analysis, visualization, modelling, implementation, and maintenance under the direction of senior team members.
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Knowledge of data visualization tools like Microsoft Power BI and familiarity with Microsoft PowerApps and SharePoint is desirable. Exposure to Azure DevOps, cloud data services (e.g., Azure Data Factory, Azure Databricks), and agile ways of working is required.
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Experience with other Data platforms like DBT, Snowflake, DeltaLake, etc. 3+ years of experience working on Spark (RDDs / Data Frames / Dataset API) using Scala/Python to build and maintain complex ETL pipelines.
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Exposure to data and data types in the Materials science, chemistry, computational chemistry, physics space a definite plus, but not required. + Knowledge of data visualization tools like Dash Apps, Tableau, Power BI, etc.
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You will work with tools/platforms like Kafka, Snowflake, and Databricks to help clients get the most out of their data that may be in systems like Salesforce, SAP, SQL Server, or file storage.
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4+ years of experience building, optimizing, testing, and orchestrating data integrations, pipelines, and cloud architectures using modern technologies such as AWS Redshift, dbt, Glue, Airflow.
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Delivery experience in Data Engineering with Google Cloud Platform including Big Query, Dataflow, Cloud Data Fusion, Cloud Composer, Dataproc, Cloud Pubsub, Cloud Function etc. + Propose, own initiatives and demonstrate though leadership that improve the efficiency and productivity of the data science Center of Excellence.
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Deep expertise in design and implementation of enterprise data store, data warehouse, data governance, data quality management, real-time data ingestion, data modeling, and metadata management, in tools such as Azure Synapses or Snowflake.
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Advanced knowledge of SQL, comfortable writing and debugging SQL queries and extracting from Azure SQL Server; knowledge of diverse data stores and data integration tools is a plus (Azure Databricks, Snowflake, Data Factory, Matillion, etc.
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5 years of experience with data science and analytics technologies such as Python, SQL, Tableau, Alteryx, AWS Redshift and Lambda, and/or Google Cloud Platform. Define and evangelize the strategy, roadmap, and execution plan to deliver new data science and analytics capabilities to enable Thermo King’s customers and achieve our company purpose while enabling rapid growth.
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Experience in DataOps, Internet of Things (IoT), Data and AI cloud solutions, Azure data factory, data lakes, databricks, synapse, and cloud-based data repositories etc. Experience with cloud-based data repositories such as Snowflake, AWS Redshift, AWS S3, Azure Data Lake, and Azure Synapse.
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Is responsible for overseeing the Council’s collection and use of census data as well as creating the Metropolitan Council’s annual population and household estimates. Experience with spatial data manipulation and analysis (for example, with geographic information systems software or R/Python.
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data job in St Paul, MN
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