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As a Developer specializing in SQL and Qlik Sense, you will play a pivotal role in advancing our data analytics capabilities and driving informed decision-making across the organization.
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Qualifications/Skills Required: Strong Python data-engineering skills (5+ years experience), including pandas, numpy,FastAPI and/or Flask Strong SQL development skills, including data warehousing concepts and development practices.
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Strong proficiency in programming languages such as Python, Java, or Scala, with expertise in data processing frameworks and libraries (e.g., Spark, Hadoop, SQL, etc.) Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS 'big data' technologies.
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In-depth experience with Power BI (Data cleaning, Modelling and visualization) ·Knowledge on SQL Server 2012 or advanced versions;SQL Server 2016 is most preferable. Job Id: 24-12506 Title: Powe BI Developer Location: Remote Duration: 12 Months JD Power BI Developer - The JD is as follows: Experienced/Expert at data visualization and advance calculations (Aggregate, Date, Logical, String, Table) using Power BI. ·Expert knowledge connecting Microsoft Power BI to various data sources.
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As a Senior Data Engineer on the MMA National IT Data and Analytics Team, we will count on you to develop and maintain scalable data pipelines, enhance data models, and provide subject matter expertise in data acquisition and consumption pipelines on Azure, Databricks and Confluent.
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And programing languages (SQL and R); SQL proficiency required in order to connect survey and 1st party data. Experience partnering with internal UX Research and Data Analytics teams to connect survey, UX insights and first-party user data and deliver integrated insights & recommendations.
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6+ years of Application development using Design Patterns, MVC, Bootstrap, React, Angular Js, JavaScript, CSS, jQuery, JSON, and XML.-6+ years of relational database design, normalization, T-SQL, stored procedures, SQL Server /, SSIS packages, SSRS Reporting, data modeling tools proficiency in data analysis and ad-hoc reporting using T-SQL, SQL Server, and Microsoft Excel.
$100,000 - $145,000Full-timeExpandUpdated Today - UpvoteDownvoteShare Job
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Certificate in business analytics, data mining, or statistical analysis, Statistical programming languages (for example, SAS, R) Languages: R, Python (Pandas, Seaborn, Scikit-learn), SQL,Hive, Pig, Impala, Sqoop, Kafka, VBA, Shell.
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Knowledge of real-time data streaming and real-time analytics Knowledge of Microsoft suite of tools is desired (Power BI, Synapse suite of analytics tools, Azure Data Factory) Strong implementation skills and working knowledge of data structures, algorithms and big data tools (Spark, Hadoop, Python, SQL, NoSQL, Hive); Must have hands-on experience using Spark.
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Hands on Experience with : R, Python, SQL, AWS (EMR, EC2, Redshift, Athena, S3, Sage Maker) Responsible to analyze the trade / transaction monitoring alert from a trading platform and apply modern data science modeling techniques to predict future disputes & anomalies to proactively manage the risk.
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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 performance as well as a detailed analytics roadmap by leveraging analytics tools (i.e., SQL/Hive/Hadoop/Cloud, Adobe Analytics, VisualIQ, Tableau/ThoughtSpot/Looker, etc.
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Demonstrated proficiency and hands-on experience in architecting, implementing, and managing Cloud-native database solutions, e.g., Azure SQL Database, Azure SQL Managed Instance and Oracle Cloud Infrastructure (OCI) Autonomous Data Warehouse, including deployment, configuration, and optimization.
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Strong experience with relational Databases, including SQL Server, and Data modeling. Dynamics 365 / PowerApps / Power BI developer w/ SQL , JavaScript. The goal is to deliver services and solutions for customers using the suite of Microsoft’s PowerApps/Dynamics platform, custom development, and data integrations on the platform.
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Data Acquisition and Transformation: Acquiring data from disparate data sources using APIs, SQL and NoSQL. Transform data using SQL, NoSQL, and Python. Use programming languages including but not limited to Python, R, SQL, Java or Scala, SQL.
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5 years of experience must include: Data analytics and statistical analysis of financial risk data; Policy and regulatory analysis; Data analytics tools including: R, Excel, and PL/SQL; Anti-Money Laundering (AML) and Know Your Client (KYC) guidelines; Oracle and relational databases; and User Acceptance Testing (UAT) and defect management.
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