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Big Data Platforms : Experience with Databricks for big data processing and analytics. Certifications : AWS Certified Solutions Architect or AWS Certified Big Data – Specialty.
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Experience with big data technologies (e.g., Azure Synapse Analytics, Spark, Databricks, AWS/Azure, etc. Minimum of 3 years' experience using Spotfire, Power BI, Tableau, and/or similar data analytics, visualization, and business intelligence tools.
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Applying knowledge and relevant work experience in Big data engineering (Hadoop, Spark, Scala, Kafka) and ETL pipeline development tools (tools: IICS/AWS Glue/Matillion/Abinitio SSIS/SnapLogic); preferable in P&C/L&A Insurance data warehouse.
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As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
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Advanced skills with Microsoft Excel (e.g. developing pivot tables, linking to external data, automating with VBA, etc. This individual will harness the power of data, critical thinking, curiosity, and communicating with impact to share insights and drive business strategy for our customers and processes to support critical initiatives that will transform the landscape of long-term care insurance.
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Background in web service development IIB and/or ADF development would be a big plus. Must have background in Data Warehousing, Oracle PL/SQL and MS SQL server development. Must also have ability to do data analysis, develop requirements and data models.
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Be part of a group of engineers building data pipelines using big data technologies (Spark, Snowflake, AWS Big Data Services like Glue) on medium to large-scale datasets.
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Experienced ETL developer with skills in IBM Infosphere/DataStage product line. The organization is looking for an individual with expertise in IBM DataStage to join their team. Experience working in Agile/Scrum process is highly desired.
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Requirements Data Engineering Python or Java AWS/GCP/any cloud Snowflake wealth asset management Upper-Intermediate English. Nice to haves Airflow; Big Query; Kafka. Requirements Data Engineering Python or Java AWS/GCP/any cloud Snowflake wealth asset management Upper-Intermediate English.
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Experience with cloud platforms (AWS), big data technologies (Hadoop, Spark) and Snowflake platform. ·Mentoring: Train and mentor junior engineers on data engineering best practices and Talend usage.
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We make use of big data and natural language processing technologies as well as dealing with day-to-day application development and scaling issues. In recognition of the growing volume and complexity of data and regulation, Exiger is committed to creating a more sustainable risk and compliance environment through its holistic and innovative approach to problem solving.
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Deloitte's tax professionals use our proprietary Depreciation Analysis & Reporting Tool (DART) to help clients drive efficient tax cost recovery calculations and planning through advanced technologies and data analytics.
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Job Description: Data Engineer Tech stack: Python, PySpark, AWS Responsibilities: Development and maintenance of data pipelines using Python, PySpark and various AWS services. Job Description: Data Engineer Tech stack: Python, PySpark, AWS Responsibilities: Development and maintenance of data pipelines using Python, PySpark and various AWS services.
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Experience with high-growth cloud, big data, data analytics, data warehouse, machine learning, or AI technologies. Existing relationships with Data Science and Machine Learning as well as Database Management industry analysts.
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Data Integration: Design and implement data integration solutions using AWS services, Databricks, and Python. AWS Data Warehousing : Strong knowledge of AWS data warehousing services, including Redshift, S3, and RDS. Programming Skills : Proficiency in Python for data manipulation and automation.
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big data jobs in Richmond, Danbury, Connecticut
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