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Hello,   Hope you are doing well !!! We are constantly on the lookout for professionals to fulfill the staffing needs of our clients, and we currently have a job opening that may interest you. Job title: Data Engineer Location: Tampa, FL (Onsite from day 1) Position: Fulltime   Job Description: • Collaborate with the project team to identify various sources of risk data. Work with data owners and understand its format, structure, and any access restrictions. • Implement procedures to extract data from various sources. This might involve writing scripts or using data integration tools to automate the data extraction process. • Cleanse and transform the extracted data to ensure consistency and compatibility with the target risk management system. This may involve handling missing values, formatting inconsistencies, and applying data quality checks. • Design and implement a data storage solution for the risk management system. This might involve selecting appropriate database technologies or cloud storage solutions based on data volume, performance requirements, and scalability needs. • Depending on the project's needs, the Data Engineer might be responsible for setting up and managing a data warehouse to store and analyze historical risk data, or a data lake for storing all raw risk data in its original format. • Implement data security measures to protect sensitive risk data. This includes defining user access controls, encryption strategies, and audit logging to ensure data integrity and compliance with regulations. • Build automated data pipelines to extract, transform, and load risk data from source systems to the target risk management system. • Schedule and orchestrate the execution to ensure data is extracted, transformed, and loaded at the desired frequency, inclusive of workflow management tools or scripting techniques. • Monitor data flow for errors or failures. Implement data quality checks throughout the data ingestion process to ensure the accuracy, completeness, and timeliness of data within the risk management system. • Collaborate with data analysts and business users to understand their risk data analysis requirements. Translate these requirements into technical specifications for data extraction, transformation, and storage. • Collaborate with Technical teams to ensure the data engineering tasks align with the overall IT infrastructure and security policies of the firm. You can share your resume at zaid@hrpundits.com or connect with me at +1 312-584-0530. #DataEngineer #Data

Technical Support #vs Data Analysis.. -------------------------------------------------- Although technical support and data analysis are distinct fields with different objectives and tasks, they share several similarities, particularly in their reliance on problem-solving, communication, and the use of technology: 1. Problem-Solving Skills:   Both technical support specialists and data analysts require strong problem-solving skills. Technical support professionals troubleshoot issues with hardware, software, and networks to identify and resolve problems efficiently. Similarly, data analysts encounter complex data sets and must employ analytical thinking to uncover patterns, trends, and insights. 2. Communication Skills:   Effective communication is essential for both roles. Technical support personnel interact directly with users to understand their technical issues, provide guidance, and convey solutions clearly and concisely. Likewise, data analysts must communicate their findings to stakeholders, translating complex data insights into actionable recommendations that non-technical individuals can understand and use. 3. Use of Technology:   Both technical support and data analysis rely heavily on technology and specialized tools to perform their tasks. Technical support professionals use help desk software, remote desktop tools, diagnostic utilities, and other IT resources to troubleshoot and resolve technical issues efficiently. Data analysts utilize statistical software, programming languages, data visualization tools, and database management systems to analyze, manipulate, and visualize data effectively. 4. Continuous Learning:   Both fields require individuals to engage in continuous learning to stay updated with the latest technological advancements and methodologies. Technology evolves rapidly, and professionals in both technical support and data analysis must adapt to new tools, techniques, and best practices to remain effective in their roles. 5. Customer Focus:   While the nature of their interactions may differ, both technical support specialists and data analysts ultimately serve customers in their respective domains. Technical support professionals prioritize delivering timely solutions to users experiencing technical issues, ensuring a positive user experience. Data analysts focus on providing insights and recommendations that enable informed decision-making and drive business outcomes, ultimately serving the needs of stakeholders within the organization. In summary, although technical support and data analysis have distinct objectives and tasks, they share commonalities in problem-solving, communication, reliance on technology, continuous learning, and customer focus. These shared attributes contribute to the effectiveness of professionals in both fields. #data_analysis #it_support #data

In reference to a early morning discussion with a #dataengineer, I realised the life for the professional involves situations where the very data systems and pipelines they design and maintain encounter unexpected issues or errors. Few examples of irony in the life of a data engineer: 1. Data Loss Prevention: Despite being responsible for data integrity and security, a data engineer might accidentally delete a critical dataset or encounter data loss due to a system failure. 2. Data Pipeline Breaks: An irony could be when a data engineer's meticulously crafted data pipeline, designed to deliver #timely #insights, breaks down just before an important board meeting or during a #critical #analysis. 3. Performance Bottlenecks: Data engineers work tirelessly to #optimize data systems for #speed and #efficiency. #Ironically, they might find that their optimizations are not enough when a sudden surge in data volume or user activity overwhelms the system. 4. Data-Driven #Decisions: Data engineers enable data-driven decision-making, but it's ironic when a decision maker ignores data-backed #recommendations and relies on #intuition instead. 5. Data Engineer's Own Data: Sometimes, a data engineer's personal data, like a collection of favorite songs or movies, might be #disorganized or #inaccessible, despite their expertise in managing complex data systems. 6. Data Engineers' Job #Security: Data engineers are essential for maintaining data infrastructure, but it's ironic when their job security depends on the prevention and resolution of issues that, if they didn't exist, might put them out of work. 7. Data Engineer's Search Results: A data engineer might encounter irony when searching for solutions to data-related problems online and finding that the search results are not well-structured or relevant. 8. Data Quality Issues: Data engineers work diligently to ensure data quality, but they may encounter irony when they discover that data quality issues in their organization's data are due to inaccurate data entry by employees in the #ITdepartment. Despite their best efforts to create robust and reliable data systems, the life of a data engineer is tough due to the constant need to manage and optimize #complex #datasystems, while also staying updated with rapidly evolving #technologies and #troubleshooting unforeseen data-related challenges.

There's a wide variety of roles involved in managing, controlling, and using data. Some roles are business-oriented, some involve more engineering, some focus on research, and some are hybrid roles that combine different aspects of data management. Your organization may define roles differently, or give them different names, but the roles described in this unit encapsulate the most common division of tasks and responsibilities. The three key job roles that deal with data in most organizations are: 1) Database Administrators manage databases, assigning permissions to users, storing backup copies of data and restore data in the event of a failure. 2) Data engineers manage infrastructure and processes for data integration across the organization, applying data cleaning routines, identifying data governance rules, and implementing pipelines to transfer and transform data between systems. 3) Data analysts explore and analyze data to create visualizations and charts that enable organizations to make informed decisions. #DataRoles #UnlockInsights #EmpowerDecisions #Data #DataEngineer #DataAnalyst

New Post: Senior Database Developer - https://lnkd.in/dxUF7Dgt Remote based in South Africa Ready to Dive into Data with a Dynamic Team? 🤩Passionate About Data Innovation with a burning curiosity for data-driven innovation? 💻 Seeking a Career in Data Excellence? About The Company Vantage Data is not just another data company, they are pioneers of possibility. Your journey is fuelled by a relentless passion for transforming data into real-world solutions that matter. What Drives Vantage Data Innovation: They thrive on pushing the boundaries of what data can do. Their team is at the forefront of turning complex data challenges into actionable insights that drive progress. Impact: Every line of code, every data point, and every decision they make is geared towards making a difference and believes that data has the power to change industries and improve lives. Collaboration: They foster a culture of teamwork, where every voice is heard and valued. Together, they tackle challenges head-on and celebrate our shared victories. Vantage Data is a community of data enthusiasts who are shaping the future. Your career here will be defined by continuous learning, boundless opportunities, and the chance to be a part of something extraordinary. Are you ready to embark on a data-driven adventure with Vantage Data? The Role In this role, you'll be at the forefront of architecting and maintaining databases critical to our success, while also playing a pivotal role in shaping our data strategies for the future. Your dedication to efficiency, innovation, and security will be instrumental in driving our data-driven initiatives forward. Masterful Database Architect: Design and construct databases with a relentless focus on achieving optimal performance. Data Guardian: Safeguard data through robust security measures, ensuring scalability and upholding data integrity across all processes and solutions. Methodical Design Application: Apply established database design methodologies, bringing rigor and structure to your work. Efficiency Guru: Determine the most effective and efficient software design strategies to meet project specifications. Project Progress Reporting: Keep the project coordinator in the loop by providing regular updates on progress against project schedules. Collaborative Partner: Collaborate closely with Account Managers, the Head of Operations, and team members to shape system maintenance, enhancements, and ongoing development. Data Integration Whiz: Streamline data import and integration processes to ensure seamless data flows. Innovation Advisor: Share insights on areas primed for improvement and stay attuned to emerging trends in software development and technologies that can empower the company. #remotehiring #remotework #remote #recruitment #recruiting #hiring #remotejob #GetRemote #GetRemoteJobs 

#hiring IT Manager, Data Modeling - Perm Role, Cleveland, United States, fulltime #jobs #jobseekers #careers #Clevelandjobs #Ohiojobs #ITCommunications Apply: https://lnkd.in/dK8bGgtN The IT Manager, Data Modeling will create and inspire a team of data modelers focused on accelerating the Digital Transformation and the adoption of a data-driven culture at a Fortune 200 Company by unlocking the maximum value of enterprise data assets. Success in this role is defined through leading a team that contributes to the larger organization by discovering, analyzing, and understanding different perspectives on data. The team will create and maintain artifacts to communicate concise and consistent data requirements from the business to IT, and within IT from analysts, modelers, and architects to database designers and API developers. The team will be measured on its ability to help the organization to understand its data assets and normalize variances to optimize business processes while ensuring data quality and consistency. This is a mid-level role. Essential Functions Strategy & Planning Actively engage with Enterprise Data Organization and Enterprise Architects to define information and data strategies as part of an overall business strategy. Understand end-to-end solutions and suggest data management solutions that will meet or exceed expectations of the customers. Ensure that data designs meet business requirements and systems goals and identify and resolve data quality and consistency issues. Cultivate a team that understands how data supports business processes and how to find gaps in data or processes and then develop strategies for improving these systems. Determine staffing capability and capacity requirements. Drive a culture of continuous process improvement. Acquisition & Deployment Analyze documentation and technical specifications of any new application under consideration to determine its data requirements. Ensure that any new data integration into company systems meets functional requirements, system compliance, and interface specifications. Contribute to discovery phase of development by evaluating proposals to identify potential data issues and make the appropriate recommendations. Contribute to business cases, make recommendations, and define success factors for data enhancements. Operational Management Facilitate discussions among data stewards, data custodians, architects and developers to ensure business, data and IT needs align. Maintain repositories for distributing data models including the entities, relationships and attributes, the information flows and business glossary. Responsible for defining the data modeling processes including prioritization, attribute identification, validation, and publication. Identify and support the tool chain needed to support modeling artifacts and deliverables. Ensures data mod

Data is an extremely valuable asset, and the company must safeguard its existence and management with the help of a data engineer. However, what exactly is a data engineer? Read more about the definitions, job descriptions, and career path of data engineer here https://lnkd.in/gzQM6JBj #DataEngineer #DataAnalyst #SEOtips

🚀 Navigating the Dynamic World of Data Management Roles In the ever-evolving landscape of data management, various roles come into play. Whether it's about business acumen, engineering skills, research focus, or a blend of these, data management roles are as diverse as they are crucial. While your organization might have unique titles or role definitions, the essence usually aligns with the common task division. 🔍 Spotlight on Three Key Data-Centric Roles: Database Administrators: These guardians of data oversee database management. They're the sentinels, ensuring data security, handling permissions, and spearheading data recovery efforts. Data Engineers: The architects behind data infrastructure, these experts handle data integration, govern data rules, and maintain pipelines that transform and transmit data seamlessly across systems. Data Analysts: These are the storytellers who transform data into narratives. Through their analyses, visualizations, and insights, they empower organizations to make data-driven decisions. 💡 Did You Know? In some companies, a single individual might juggle multiple data roles. Imagine being the database admin setting up a database and then switching hats to a data engineer, crafting a pipeline for data transfer! 🌐 Roles Explored: Database Administrator: They're not just about maintenance; they're about innovation in database design, ensuring optimal performance and robust recovery strategies. Data Engineer: Beyond just managing data, they're at the forefront of designing and implementing complex data workflows, ensuring data integrity and privacy across various platforms. Data Analyst: More than just number crunchers, these analysts unlock the stories hidden within data, enabling businesses to glean actionable insights. 🔥 The Big Picture These roles, while distinct, collaborate to form the backbone of effective data management. Understanding their nuances helps us appreciate the complexity and importance of data in today's digital world. 📢 Let's discuss: How do these roles manifest in your organization? Are there any unique blends or overlaps in responsibilities? Share your insights! #DataManagement #DatabaseAdministration #DataEngineering #DataAnalysis #ITRoles #DigitalTransformation

Are you a business with a strong engineering team but in need of high-quality data models without the commitment of a long-term contract? I had a fantastic call this morning with a Data Architect I’ve known for a while now, who, like many, has been struggling to land a contract in this challenging market. We got on to the subject of Data Modelling, an area he’s a sh!t hot in. He asked if I ever get requirements for ad-hoc Data Modellers, which I don't, but it did get me thinking … I bet there are really good engineering teams out there but they’re lacking good quality models to build from … ?? hmmmmm What are the benefits to this: · Get the data models you need, when you need them, without long-term commitments. · Pay only for the specific models you require, saving on full-time hiring costs. · Access top-notch data modelling skills to ensure your data is well-organised and ready for action. · Receive high-quality models faster, enabling your team to focus on core tasks. · Enjoy the peace of mind that comes with professional, well-structured data models. Whether you're building a new project or optimising an existing one, trust me, this chaps data models will help your engineering team take off! Interested? You know what to do ... eric.wright@accessplc.com #DataModeling #DataArchitecture #BusinessIntelligence