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10 years of experience in data engineering, data architecture, BI & Analytics, and/or Data Science. Execute the HW Analytics Strategy that includes building a modern Unified Data Warehouse, expanded Self-Service, and Data Science capabilities.
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Reporting to the VP of Data Science and Machine Learning, this person will be responsible for leading a team of data scientists who are aligned by therapeutic areas and support the brands (marketing and sales teams) in their strategy and execution.
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Must have experience building Data Lake and data warehouse solutions using ETL, and ELT pipelines on any of Databricks, Snowflake, Azure Data Lake, and similar data lakes. Hands-on experience designing and building streaming data pipelines using Airflow, Kafka, Event Hubs.
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Proven data science and data engineering skills including machine learning, natural language processing, graphs, data pipelines, data lake, data visualization.
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Proficiency in SQL and experience with modern data processing frameworks and tools (e.g., Hex, Python, R, Tableau, Power BI, Hadoop, Spark). Experience with cloud-based data platforms and data warehousing solutions (e.g., Snowflake, Redshift, BigQuery.
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Hands-on experience with AWS and cloud-based data services and solutions (e.g., Snowflake, Databricks). Hands-on experience with data processing frameworks like Apache Spark or Apache Flink.
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Design and implement scalable and robust data models, databases, and data integration solutions to meet business requirements. Define data standards, policies, and best practices to ensure data integrity, security, and governance.
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Stay updated on advancements in data science, machine learning, and analytics. Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
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Ability in data science languages/tools such as SQL, R, SAS. Proficiency in the design and implementation of modern data architectures and concepts such as cloud services (AWS, Azure, GCP), real-time data distribution (Kafka, Dataflow), and modern data warehouse tools (Snowflake, Databricks.
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With over two decades of experience and boasting alumni from AWS and Cognizant, our expertise spans AI , Machine Learning, Data Science , Data Mesh and Compliance Automation across platforms like AWS, Azure, and GCP. Our exclusive tools, CompQ and DataCube, simplify and expedite solution implementation, helping clients save significantly.
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Familiarity with cloud data warehousing solutions (e.g., Snowflake, BigQuery, Redshift). Data Engineering:Expertise in cloud-based data services and platforms (e.g., AWS, Azure, Google Cloud.
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These products include Purview for data governance, Power Apps & Automate for low code/no code application development, Azure Data Factory for ELT, Power BI for data visualization, and more.
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You understand master data management, data governance and data catalogs. You can design and build cloud-based solutions (such as AWS, Azure, GCP, Snowflake) utilizing data warehouses, databases, machine learning and business intelligence.
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Tool & Technologies: You’ll program in Java and model data using Pure/Legend – a data management and data governance open source platform that we will teach you. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action.
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We are building the data foundation of Web3—a fully decentralized and community-operated data warehouse, leveraging innovative cryptography to connect tamperproof query results directly to smart contracts.
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data science jobs Company: Soliant in Snowflake, AZ
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