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Apply data from BSA/AML Compliance Department stakeholders to translate qualitative risk factors into responsive risk models that leverage new technology. · Develop knowledge of new analytical techniques and data sources that provide ongoing risk mitigation, and how emerging data and technology issues may impact the achievement of BSA/AML Compliance Department’s objectives.
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Experience in developing Data Warehouse/Data Marts using, as examples, OBIEE, OBI APPS, Cognos, Business Objects, SPSS, SSIS, SSRS, Informatica Power Center, OWB and ODI. · Experience on design and development of Data Warehouse Architecture for Enterprise Data Warehouse (EDW), Operational data Store (ODS), Operational Data Marts and Data Marts.
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This role is a unique opportunity for an experienced ML scientist and hands-on NLP/Gen AI/ LLM senior scientist to grow into the next step in their career journey and apply her or his domain expertise in NLP, deep learning, GenAI, and LLMs to drive business value for multiple stakeholders while mentoring and growing a ML Data Science team.
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Experience working with data SaaS and BI tooling (Fivetran, Looker, Databricks, etc.) Stay current with emerging trends and technologies in the data engineering field, incorporating them into the organization's data strategy.
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Experience with inferential statistics, structured decision support, RPA & automation, machine learning + AI, health data interoperability. Experience in data product development at enterprise scale, including on cloud platforms, Spark or other big data ML systems, and comfort using Jira, Slack, Teams, and other collaboration tools.
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In-depth knowledge of big data technologies such as Hadoop, Spark, Kafka, and cloud platforms such as AWS, Azure, GCP, Snowflake, Databricks, etc. Preferred Qualifications:Professional certifications in cloud computing (e.g., AWS Certified Solutions Architect, Microsoft Certified Azure Solutions Architect, Azure Data Engineer, SnowPro Core) and/or big data technologies.
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Minimum 7 years of designing and implementing an operational production grade large-scale data solution on Microsoft Azure Snowflake Data Warehouse. Strong understanding or Snowflake on Azure Architecture, design, implementation and operationalization of large-scale data and analytics solutions on Snowflake Cloud Data Warehouse.
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Experience in traditional and large scale distributed data processing (e.g. Spark, Dataflow, Airflow). Experience designing data models and data warehouses and using SQL database management systems.
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Certifications like Data Engineering on Microsoft Azure (DP-203) or Databricks Certified Developer (DE) Certifications like Data Engineering on Microsoft Azure (DP-203) or Databricks Certified Developer (DE) are.
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Be a key resource for research and data analytics on topics pertaining to faith-based property development and community development and impact. Conceptualize and develop business plans, financial models, research, dashboards, data analytics, and presentations to support individual transactions and the overall portfolio of grants and mission investing.
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Identify opportunities to leverage technology to improve ability to compile, analyze, and report item creation and data (e.g. smartsheet, access, excel, JDE, Cantor, AQ, etc.) Implement data governance processes for item master data maintenance.
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Experience with an MPP Data Warehouse such as BigQuery, Oracle Exadata, Redshift, or Teradata. The Senior Data Engineer will be responsible for accelerating and solidifying the Data Engineering team’s development, deployment, and operational support practices by building tools leveraged by the entire Data Engineering team.
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Utilize programming languages like Java, Scala, Python and Open Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake. 2+ years of data warehousing experience (Redshift or Snowflake.
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Experienced in using Big Data stack (Hadoop, Hive, Spark, Kafka, Airflow/OOZIE, BigQuery/Presto/Impala, etc.) At this stage, this role is pivotal as we are taking this solution to the next level and positioning it as the core product for everything marketing - audience segmentation, statistical testing, data governance, data distribution, revenue optimization, and much more.
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Experience with cloud computing platforms (, AWS, Azure, GCP) and cloud native computingProficiency in programming languages like Python, Java, Scala, C#, SQLExpertise in big data technologies such as Hadoop, Spark, Kafka, and NoSQL databasesKnowledge of data modeling, ETL processes, and data warehousing conceptsExceptional problem-solving abilities and teamwork skills.
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Title: data Company: The Lubrizol in New York, NY
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