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Develop and optimize big data processing using Spark and PySpark within the Databricks environment. Design, build, and maintain scalable and reliable data pipelines using Infrastructure as Code (IaC) principles and Databricks along with Datadog.
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Best-in-Class Tech Stack: Work with top-tier tools like Segment, mPartical, PowerBI, Tableau, Microsoft Azure, Google Big Query, Python, Google Workspace, Slack, ClickUp, Zoom and more ensuring you have the resources you need to excel in your role.
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You will design, develop and automatesecure, robust, and high-performing data platform solutions to driveCAISbusiness growth using Python, Kotlin, Snowflake, DBT and Kubernetes. Extensive experience with DBT and Snowflake for data warehousing, demonstrated through the creation and management of complex SQL/ETL/ELT data workflows.
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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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Onboard datasets, explore data, and automate tasks using a modern Python data stack. Experience with financial datasets (e.g. Refinitiv, S&P, Bloomberg) is a big plus. Hudson River Trading (HRT) is looking for a Data Production Engineer to join our Data team.
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Must include one year of experience in each of the following: (1) working with complex data structures and large datasets in a real business setting; (2) utilizing SAS, SQL, Excel, VBA, PPT, Tableau, Visio, MARS and CART software; (3) delivering oral and written data analytics presentations to clients, senior managers and executives; (4) big data processing, data extraction, and variable reduction; and (5) managing analytics projects with global resources.
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Senior Data Engineer (Python, Kafka, Databricks, AWS) 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.
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You must be passionate about data management with a solid background in AWS, Databricks, Python, Trino/Starburst, Databases and SQL.Design, develop, monitor, and maintain data pipelines in an AWS Gov Cloud ecosystem with AWS, Databricks, Delta Lake and Trino as the underlying platforms.
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And health interoperability standards (HL7, FHIR, USCDI) preferred Experience working with real-world data sources such as EHR and claims data Familiarity (able to mostly read) with common data analysis tools and platforms (e.g., SQL, Python, R.
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Proficiency using leading software vendors for financial data and fixed income modeling, including Bloomberg, Aladdin, Intex, Trepp, and others. Proficiency in programming languages and tools such as Python, R, SQL, MATLAB, C.
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AWS, Redshift, Snowflake, dbt, Databricks, Python. The ideal candidate will have a strong background in AWS, Redshift, Snowflake, dbt, Python, building ETL pipelines, and Machine Learning.
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Experience building loan-level credit/prepayment models from data preparation, data analysis, and model estimation through deployment into productionExperience with generalized regression models as well as machine learning frameworksVery strong programming and software design skills (Python, C.
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Experience may be gained concurrently and must include one (1) year in each of the following:-Building statistical models and machine learning models using large datasets from multiple resources-Working with Customer, Content, or Product data modeling and extraction-Using database technologies such as SQL or ETL-Applying specialized modelling software including Python, R, SAS, MATLAB, or Stata.
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Experience with audience tools such as SCOUT (Mediahub quantitative surveying), Comscore, MRI, Exact Target; creative/brand evaluation and tracking tools like Kantar Millward Brown, Nielsen Brand Effects, YouGov, Dynata, Survata; search tools like Adwords, Kenshoo; social tools like Crimson Hexagon, Netbase.
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Forms part of the Analytics Open Hub Global Data and Analytics team to deliver the strategy, execute plans, providing specific and deep expertise in data design and modelling, data warehousing, big data platforms and data engineering.
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