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Develop, deploy and maintain data processing pipelines using cloud technology such as AWS, Kubernetes, Airflow, Redshift, Databricks, EMR. Experience with data warehouse platforms such as Redshift, Databricks, Big Query, Snowflake.
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YOUR SKILLS AND EXPERTISEBachelor’s degree in computer science, data science or a related field with five (5) or more years of working as a data engineer, ETL developer and/or data warehouse DBA.STANDOUT QUALIFICATIONS:Experience with Cloud-based data services and solutions (Azure Synapse / Data Lake, AWS RedShift, Snowflake, GCP Big Query)Experience partnering with Analytics and Data Science teams in building out production grade GenAI/ML solutions.
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Experience in programming languages (such as Python or C#) and familiarity with SQL required Experience deploying data/code to cloud computing platforms (such as AWS, Azure, Google Cloud) and their data analytics services preferred.
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Experience with cloud-based quantum computing platforms (e.g., Google Quantum AI, IBM Quantum Experience). Knowledge of machine learning and its applications in quantum computing.
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Experience with big data tools and architectures, such as Cloudera Hadoop, HDFS, Hive, and Spark. THE ROLE:As a key member in the Advanced Data Analytics team, the Data Analyst will work with this and a cross-functional team to develop and execute the data analytics strategy and apply to Oshkosh Corporation products.
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Ability to design large scale distributed Big Data processing systems using technologies such as Hadoop, Spark, Kafka, etc. You have deep expertise building scalable data analytics and machine learning architectures and deploying them seamlessly in Cloud-native environments.
$210,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Integrate data platform infrastructure with other systems fostering seamless collaboration among teams e.g. system integration with Fivetran, Monte Carlo, Salesforce Data Cloud, Tableau, Looker, Teradata, Bigquery.
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In our consultative approach, we are platform agnostic and are committed to accelerating the development of innovative AI solutions for our clients with the best possible tools; this spans all relevant technologies from on-prem and cloud deployment, high performance computing, automation, DevOps, MLOps, data engineering and streamlining IT infrastructure processes.
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2-3 years of experience in defining enterprise data strategy in the areas such as AI, data management, data governance, data supply chain, data security, data archival, data quality, master data management, data architecture, automation and/or cloud data migration for medium to large scale corporations.
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Interest in predictive analytics, data fusion, big data processing, and/or edge processing and experience building enterprise scale cloud-based analytics platforms with GIS data analytics and visualization.
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In this hands-on role, you will architect and engineer data pipelines, platforms, integrations, and products on modern cloud platforms, such as Snowflake, Databricks, Azure, and/or GCP. Collaborating closely with the data leadership team, you will shape the long-term vision, cloud adoption roadmaps, future-state analytical architecture, and data governance frameworks necessary for this transformation.
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Proficiency in big data technologies, cloud computing, machine learning, and AI. Experience with big data technologies such as Hadoop, Spark, and Kafka, and cloud-based data platforms such as Amazon Redshift, Google BigQuery, or Azure Synapse Analytics.
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Provide in-depth knowledge of GCP data services (Big Query, Cloud Storage, Dataflow, Looker/Tableau etc.) Extensive experience in data warehousing, data management, and business intelligence with proven expertise in Google Cloud Platform (GCP) and its data services (Big Query, Cloud Storage, Dataflow, etc.
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The courses may include Foundations of Data Analytics and Programming, Advanced Excel for Data Analytics, Data Governance, Management and Quality, Data Visualization-Power BI, Data Visualization-Tableau, Data Privacy and Integrity, Data Protection, Descriptive Analytics, Predictive Analytics, Data Complexity, Cloud Analytics, Big Data, various programming courses and concepts involving python, r and ML, and database courses (including MySQL, Microsoft SQL Server and NoSQL alternatives.
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Big Data Technologies: Hadoop, Spark, Athena, materialized views. Data Visualization: Tableau, Looker, Power BI, Quicksight. Cloud Platforms: AWS (EC2, S3, RDS, Lambda, CloudFormation, VPC, IAM, Redshift.
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big data cloud computing jobs Title: data scientist Company: All It Solutions in Phenix-city, Alabama
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