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Learns about machine learning, data science, computer vision, artificial intelligence, statistics, and/or appliedmathematics as necessary to carry out role effectively. Experience with designing and maintaining data warehouses and/or data lakes with big data technologies such as Spark/Databricks, or distributed databases, like Redshift and Snowflake, and experience with housing,accessing, and transforming data in a variety of relational databases.
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Experience in developing & building high to medium complex data pipeline for Enterprise Data Hub using ADF, Databricks, dbt, Azure Cloud Services, MS SQL Server ADW/DB, Python, Pyspark, Devops.
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Experience implementing CI/CD pipelines using DevOps tools in GitHub/Azure DevOps. Experience with Data Modeling – Dimension and Facts tables, snowflake schema. Experience delivering solutions and insights on the Microsoft Azure platform with exposure to Azure Databricks, Azure Synapse, Azure Data Factory, PostgreSQL, Azure SQL DB, Power BI or Azure ADLS Gen2.
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Working knowledge of tools like Jira, Confluence, Azure DevOps, ServiceNow. Understanding and ability to implement Robotic Process Automation (RPA) and Machine Learning (ML) solutions to advance capabilities in Artificial Intelligence (AI.
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Experience in data science, statistical analysis and modelling data using leading Artificial Intelligence and big data tools (e.g. TensorFlow, R, Python, Azure SQL Server & ML Studio, Databricks, Python Power BI, etc.
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The client is looking for a Senior Azure ETL developer to ingest/transform and load Data Assets and implementation of a cloud-based data management platform that will support the agency.
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Our products are trusted by leading companies including PayPal, Visa, FTX, Uniswap, Anchorage, and federal agencies such as the FBI and IRS. Every day, we tackle challenges in data engineering, data science, and threat intelligence to advance our mission to build a safer financial system for billions of people.
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This role involves managing the deployment automation of Azure PaaS/SaaS services within a Big Data & Analytics platform, ensuring platform stability and compliance with IT security requirements.
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Minimum 5 years' experience in data engineering with a proven track record in the Azure ecosystem and with Azure DevOps. Design and implement complex data models on Azure Synapse Analytics to support data warehousing and big data solutions.
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Total Talent Solutions, Workforce Solutions, Contingent Workforce Solutions, Outsourcing & Consulting, Tech Consulting Services, Independent Contractor Services, Software Engineering Solutions, Technology Staffing & Solutions, Customized Training and Talent Development, Project-Based Services, Cloud Enablement and Migration, IT/Software Development, UX Design, Data Science, Product & Program Management, Data Science, Quality Engineering, Big Data Services, Automation, and Telecom.
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Minimum 5 years’ experience in data engineering with a proven track record in the Azure ecosystem and with Azure DevOps. Minimum 5 years’ experience with Data Modeling, ETL, and Data WarehousingMinimum 3 years’ hands on experience with Azure Services.
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Energy Sciences, Biosciences, Physical Sciences, Computing Sciences, Nanotechnology, Supercomputing, Big Data, Energy Innovation, Science, Climate Change, exascale, computing, environmental science, materials science, Artificial Intelligence, AI, Machine Learning, Climate, Supercomputing, and Basic Science.
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NTT DATA's data and artificial intelligence team partners with the world's largest organizations to simplify their most complex challenges and transform their data into a competitive advantage.
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Big Data technologies, Azure, AWS, Hadoop, Spark, Hive, Kafka, Flume, NoSQL stores (HBase, Cassandra, DynamoDB, MongoDB). Data Visualization Solutions: MS Power BI, Looker, Tableau, Azure Streaming Analytics, Data Lake Analytics, Azure Time Series Insights, Azure Synapse Analytics.
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Must have a strong background in one or more of the following: Mathematical, Statistics, Probability, Deep Learning, Machine Learning, Natural Language Processing, Computer Vision, Recommendation Systems, Pattern Recognition, Large Scale Data Mining or Artificial Intelligence.
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big data artificial intelligence azure devops jobs Title: developer
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As the job market remains highly competitive, we have seen a surge in "rage applying." This is when candidates apply to multiple jobs, often without considering whether they are truly interested in the role. Rage applying goes hand-in-hand with quiet quitting. Often, employees want to entertain the thoughts and feelings of leaving their job, but they aren't necessarily serious about leaving yet. Meanwhile, other employees engaging in this trend are actually trying to find a better role. As a recruiter, it can be hard to identify who are the real applicants in a sea full of quiet quitters, but understanding rage applying and identifying red flags will certainly help.
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In today's competitive job market, writing quality job ads is critical for attracting top talent to your organization. While networking and candidate referrals are prime real estate for finding qualified candidates, nothing beats the tried-and-true method of writing an extraordinary job ad. But while writing a great job ad is the first step, what's more important is increasing visibility. You could have the most detailed, well-written ad on the internet, but if no one sees it, then you are wasting time (and potentially money!). Employers often believe that job boards are the root of the problem, but you can learn how to increase job ad exposure by tweaking a few steps of your recruitment process.
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Building a candidate pipeline through a great internship program for local college students and recent graduates at local universities is a great and cost-effective way to attract and retain top talent. By offering meaningful and impactful work experiences, regular feedback, coaching, and mentorship, you can create a positive internship experience that will make your organization a sought-after destination for future employees. This not only benefits the organization in the short-term but also in the long-term, as you'll have a pool of well-trained and experienced candidates who may be interested in full-time employment once they graduate. Furthermore, building relationships with local universities and college students can increase brand awareness and build a positive reputation for your organization in the local community.
Hiring Transparency
Transparency in hiring refers to the open and honest communication and information sharing that takes place between employers and job candidates. It encompasses all aspects of the hiring process, from posting job descriptions to providing feedback on performance during and after the interview process. In today's job market, hiring transparency has become increasingly important for both employers and candidates alike.
Recruitment strategies that are weird, but actually work
In the current candidate-driven job market, recruiters are looking for unique ways to attract talent. Some have resorted to even (dare we say it?) recruitment strategies on the border of weird and wacky. What can we learn from the unusual recruitment tactics that are being used and actually getting results? Here’s a rundown of some unique recruitment strategies that actually work.