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Your expertise in ETL, Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks will be essential in ensuring efficient data processing and analysis. Design, develop, and implement end-to-end data pipelines, utilizing ETL processes and technologies such as Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks.
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Hands on experience of building data pipelines using Apache Spark (Azure Databricks), Scala. Job profile : Data Engineer experience on Spark with Scala / Azure Databricks. Hands on experience in designing and delivering solutions using the Azure Data Analytics platform including Azure Storage, Azure SQL Data Warehouse, Azure Data Lake.
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The Modeling and Simulation Data Scientist will support the Combination Product Operations organization by improving the way. " Partner with multi-discipline digital teams (data analysts, data engineers, data scientists, and business product owners) to advance data analytics tools/features (such as predictive/ prescriptive algorithms and machine learning.
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As the Data Scientist, you will use Google Cloud Platform (GCP) tools and technologies, such as Vertex AI and BigQuery, to build, deploy, and monitor scalable and robust machine learning solutions.
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Experience with any ETL and Data Visualization tools will be a plus. We are looking for an experienced and talented technical individual to join our team as Cloud DevOps Engineer to support our Cloud Data Management and Advanced Analytics platforms.
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For data visualization (i.e., SPSS, SAS, MatLab, Tableau, etc. We are currently seeking a Data Scientist to work for our company. in assisting in the analysis and interpretation of a wide range of data to.
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WSDOT’s Public Transportation Division (PTD) is seeking a currently enrolled college student or recent graduate to fill an internship position in data analytics. Enrolled in or a recent graduate of a bachelor’s degree program in transportation planning, environmental planning, urban planning, regional planning or land use planning, engineering, data analytics, public administration, communications or related field at an accredited college or university.
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Keywords: GCP, Google Cloud Platform, BigQuery, Composer, SQL, Python, Data Engineering, Data Pipelines. Experience working with Airflow as workflow management tools and build operators to connect, extract and ingest data as needed.
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Design and optimize data structures in data management systems (Snowflake, GCP, HANA) to enable reporting analytics using Tableau/Power BI as well as AI/ML solutions. 5+ years building scalable ETL pipelines with big data processing and/or developing applications and data sources (Apache Ni-Fi, Airflow, SSIS.
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Extensive hands-on experience implementing data migration and data processing using AWS services: VPC/SG, EC2, S3, Autoscaling, CloudFormation, LakeFormation, DMS, Kinesis, Kafka, Nifi, CDC processing Redshift, Snowflake, RDS, Aurora, Neptune, DynamoDB, Cloudtrail, CloudWatch, Docker, Lambda, Spark, Glue, Sage Maker, AI/Client, API GW, etc.
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Experience reviewing in-vivo and in-vitro data including, but not limited to, inhalation, pathology, chemistry, PCR, and ELISA. Mentor and train junior staff in Data Coordinator duties.
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Develop and oversee a comprehensive data architecture, aligning with business goals and integrating technologies such as Azure, Databricks, and Palantir to craft a forward-looking data management and analytics landscape.
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Knowledge of predictive analytics techniques (e.g., predictive modeling, statistical programming, machine learning, analytics, data visualization). Experience in data visualization tools such as Google Looker, MicroStrategy, Kibana.
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We are seeking a Senior Data Analyst to help develop MLT’s insights on advancing racial equity and socioeconomic mobility. Bachelors in mathematics, statistics, data science, or social science.
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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.
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