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Experience developing with data SaaS and BI tooling (Fivetran, Looker, dbt, Databricks, Apache Airflow, etc.) 6+ years of experience in data engineering working with big data systems that can process and transform data at scale.
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Integrate Snowflake with existing systems, data sources, and BI tools (e.g., Tableau, Power BI). Cloud platform certifications (AWS Certified Solutions Architect, Microsoft Azure Data Engineer, etc.
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Experience using the Power Platform Suite, including Microsoft Power BI, Power Apps, and Power Automate. Leverage proficiency with AWS services, including Amazon S3, Amazon RDS, Amazon RedShift, Amazon ElasticSearch Service, Delta Lake, Neo4j, and Parquet for data storage, processing, and retrieval.
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Proficient in SQL, Python, and data visualization tools like Looker or Power BI. Familiarity with big data technologies like Apache Hadoop and Spark. Certifications: Google Cloud Professional Data Engineer or Professional Cloud Architect certification preferred.
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2 years of experience on data visualization tools such as Tableau, Power BI, R Shiny, D3. Proficiency in large scale data query using SQL, scripting language using Python, statistical tool using R, and data visualization tools (e.g., Tableau, Power BI.
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Support data migration, integration, and other related projects involving HubSpot CRM, Sage 100 ERP, and Power BI. A critical component of this role is the required knowledge and experience with HubSpot CRM , Sage 100 ERP , and Power BI for data visualization.
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Proficient in data querying and visualization tools (examples may include SQL, Python, Power BI, Spotfire, etc). Proficient in data querying and visualization tools (e.g., SQL, Python, Power BI.
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Proficiency in spreadsheets (e.g. Excel, Sheets) and slide creation tools (e.g. PowerPoint) is required with data visualization (e.g. Looker, Tableau, Microsoft Power BI etc.) Working with partners to improve transfer success rates by analyzing partner data to identify initiatives that reduce issues or declines.
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Data Visualization Tools (e.g., Tableau, Power BI, Plotly) Apache Hadoop or Apache Spark (for big data processing) Data Warehousing (e.g., AWS Redshift, Google BigQuery.
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Natural Language Processing (NLP) Tools and Frameworks (e.g., Hugging Face, AWS Comprehend Medical for extracting insights from clinical text data) Docker, Kubernetes, ECS, EKS or AWS Fargate (for containerization and orchestration of data applications and reproducibility.
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The Data Scientist will be responsible for driving insights from the vast amounts of patient and environmental data available within our data warehouse. HIPAA Compliance (handling sensitive patient data securely.
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Data Privacy (understanding of privacy laws such as HIPAA, GDPR) Work closely with researcher teams to design analysis specifications, including input data specifications, data cleaning, algorithms, and interpretation of results.
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Data Scientist (Healthcare) 100% Remote. Data Science & Machine Learning Frameworks. Python (for preprocessing, data analysis, machine learning, scripting) Data Governance & Security.
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Develop and implement algorithms on existing data warehouse records and identify new external data sources to be ingested to the data warehouse to strengthen analyses. Research and implement AI algorithms, apply off-the-shelf AI and data-centric tools, and collect, store, and maintain data.
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Auditing & Compliance Tools (for ensuring secure and compliant data handling) SAS (common in healthcare data analysis) Data Anonymization or De-identification techniques (for research and compliance.
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big data power bi jobs Title: data engineer Company: Dice in Pelham, New Hampshire
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