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Proficiency in scripting and programming languages (Arcade, Python, R, SQL, Java/React. Lead the development and refinement of a comprehensive GIS data strategy for law enforcement/public safety and security focus, addressing data silos, security/access requirements, data governance/quality, and metadata documentation.
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Strong understanding of data warehousing concepts, SQL, SSRS and data integration, Experience with data governance, data security, and compliance regulations, Manage data extraction, manipulation, transformation and aggregation; evaluate user requests for new or modified programs and development of related business models.
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Must have strong experience with data warehouse in SQL Server and AWS – Databricks or RedShift. Must have experience with Microsoft SQL Server in Linux OS, OpenShift Docker container and AWS. Automation is essential for all aspects of enterprise database administration.
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A critical thinker with strong analytical skills; Must be proficient with Excel, SQL, and data visualization tools such as Tableau or Looker. Excellent written and verbal communicator; you have the ability to tell a story combining data with qualitative insights, and you understand how to tailor your communication to any audience.
$130,000 - $160,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Hands-on development experience with Snowflake features such as Snow SQL; Snow Pipe; Python; Tasks; Streams; Time travel; Zero Copy Cloning; Optimizer; Metadata Manager; data sharing; and stored procedures.
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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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Experience with SQL and NoSQL based databases for storage and processing of structured, semi-structured & unstructured data. Programming Language: Python, R, SQL, Java, Scala, Pyspark/Apache Spark, Shell scripting.
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Python, SQL, SSIS, Fixed Incomes, Quantitative Finance, Risk, Var, stress test, trading. The ideal candidate will have expertise in quantitative finance , particularly in Fixed Income products , and possess strong programming skills in Python , SQL, and SSIS.
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Design & develop data pipelines end to end using Spark SQL, Java and AWS Services. Cloud implementation experience with AWS including: + AWS Data Services: Proficiency in Lake formation, Glue ETL (or) EMR, S3, Glue Catalog, Athena, Kinesis (or) MSK, Airflow (or) Lambda + Step Functions + Event Bridge + Data De/Serialization: Expertise in at least 2 of the formats: Parquet, Iceberg, AVRO, JSON-LD + AWS Data Security: Good Understanding of security concepts such as: Lake formation, IAM, Service roles, Encryption, KMS, Secrets Manager.
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You have passion and expertise in one or more of the following areas: risk analytics, data analytics, machine learning, SQL, Python, cloud security, network security, vulnerability management, data protection, threat intelligence & investigations, and identity & access management.
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Collecting/cleaning/analyzing substantial customer and sales data using SQL and/or BigQuery. Well-versed in core advanced analytics data mining and scripting tools such as Python, R, and SQL.
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Using Oracle SQL developer data modeler; and performing data visualization and KPI dashboard development, using Tableau and Python libraries. DE analyzing large data sets to gather insights, develop new processes, perform calculations, identify anomalies, and produce new reporting capabilities; traversing and extracting data from data-base schemas across diverse content sets, using SQL; and delivering data visualizations using R and Python.
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You have hands on experience with data visualization and reporting tools such as Tableau, R Shiny, and/or Looker. You will be responsible for building out a holistic view of seller risk performance, identifying potential risks and supporting controls by leveraging analytics insights and tools (i.e., SQL/Hive/Hadoop/Cloud, Adobe Analytics, VisualIQ, Tableau/ThoughtSpot/Looker, etc.
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High Level of digital literacy, ability to work efficiently with MATLAB, Excel (VBA), SQL, R, Python or C. Excellent written and verbal communication and presentation skills, ability to communicate quantitative concepts to financial professionals Knowledge of prepayment modeling, MBS pricing and risks is a plus Knowledge and experience on data science and Machine Learning technics/languages is desired SEC Covered Clearing Agency Standards Additional Qualifications.
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Moderate to advanced analysis expertise of end-to-end processes, leveraging tools and techniques for presenting and analyzing data including, rest API technologies, SQL, JSON, Postman/Insomnia.
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