DAS42’s Post

#hiring Data Governance - Senior Consultant, New York City, United States, fulltime #opentowork #jobs #jobseekers #careers #NewYorkCityjobs #NewYorkjobs #HealthcareMedical Apply: https://lnkd.in/g7wnNsbq Job Family:Digital ConsultingTravel Required:Up to 25%Clearance Required:Ability to Obtain Public TrustWhat You Will Do:Conduct interviews with client stakeholders to assess current metadata management and data governance capabilities and refine use cases associated with metadata management, taxonomy, and ontology development.Translate these use cases into requirements to communicate to the technical implementation team to implement into Collibra.Collaborate closely with business stakeholders to ingest and analyze existing data dictionaries, business glossaries, and taxonomies to determine the existence of metadata gaps, alignment with controlled vocabularies, and potential contribution to increase usability, reliability, and search/discoverability of data assets associated with the Collibra adopters' use cases.Provide guidance in setting the relevant workflows, roles, views, audit reports, and other execution and monitoring concepts within Collibra to support governance of the data inventory development.Provide guidance in supporting lineage creation in Collibra.Provide guidance in developing roles and permissions to support cross-community collaboration for managing and governing assets

If you have been munching data from all dimensions for more than 15+ years and shifting from RDBM to Warehouses to Data Lakes, now living in your fancy Data Lake House, We may help you flow the data in you.   But , what we are not looking for must come first : - Only delivery or project management experience of data engineering or similar large scale projects. - If you had few data engineering crash courses and you believe "You are all set". - Speak for hours on how "Data is the new Oil" ,but struggle "To get started"   Looking for a Senior Leader in Data Engineering - At least 15+ yrs of total experience, 10+ in Data centric and modern data engineering tech roles. - Have lead meaningful discussions with C suite tech executives on areas of data engineering - Can take an ideation to execution alongside the solutioning team in areas unexplored. - May not know all , but can figure out limitations of any in days( not weeks) Won't own delivery but shall be responsible for quality of delivery through solutions. - Can sniff opportunity from a barebone problem statement and draw a blueprint. - Can Design learning roadmap of an expert team of data engineers for future readiness. - Extensive experience to Snowflake and it's industry counterpart is must. - And Your face brightens up at the whisper of the following : " Snowflake, ETL, data centralization, data lineage, Databricks , Python ,Data Quality Enhancement, Data Consolidation, Data Governance and Security ,Data Lineage, Datahub tool "   No harm exploring , drop me a note for a friendly chat.  #dataengineering #datalakehouse #snowflake

Data Architect opportunity with international NGO

🔍 What does an Analytics Engineer do? 💡 An #AnalyticsEngineer works at the intersection of #data #engineering and #analysis, transforming raw data into clean, well-structured #datasets that drive #business decisions. By leveraging #tools like #SQL, #dbt, and #cloud platforms, they ensure data pipelines are accurate, scalable, and reliable, empowering teams with the #insights they need. 📊 🚀 If you enjoy working with data and solving complex problems, this dynamic role could be a perfect fit for you!  🫵 Our next Analytics Engineer #training starts on October 1 or November 5. Interested?  Download the full job description (link in the comment section) to learn more!

🔍 Data Architect vs. Data Governance Manager: What's the Difference? 🔍 In the world of data, roles can often overlap and get confusing. Let’s clear it up! 📐 Data Architect: Designs and builds data systems and structures. Think of them as the blueprint creators for data management. 🛡️ Data Governance Manager: Ensures data quality, security, and compliance. They are the guardians, making sure data is used correctly and safely. 💬 Your turn: How do these roles interact in your organization? Share your experiences, challenges, and insights in the comments! 🚀 Let’s demystify these crucial roles together and strengthen our data-driven community! #DataArchitecture #DataGovernance #DataRoles #CommunityEngagement #DataManagement

In today's digital world, data architects are more essential than ever. With data booming across all industries, businesses need professionals to design and manage complex data infrastructures. In the UK, sectors from banking to healthcare are seeing a surge in hiring data architects. TechNation reports a 25% increase in job postings for data architects in 2024 compared to last year. 📊 This spike makes sense, given the critical need for seamless data management and advanced analytics to stay competitive. From my experience, the shift to cloud-based solutions has further amplified this demand. Data architects now play a pivotal role in leveraging big data, machine learning, and AI for business growth. Data architects, I'd love to hear from you! How are you finding the market? #DataArchitecture #TechTrends #BigData

Hiring A Data Architect 1. Understand the complexity of the job. A great data architect is used to managing 1,000 data points concurrently on multiple levels - it is like a multi-dimensional array. They can sense the impact from any one change to the far reaches of the grid, and they can manage concurrent changes. If something goes wrong they can point you to where you should be monitoring and triaging. Any time you want to integrate new architecture they can tell you what will work and what will break. It is a very complex skill set that is a combination of natural talent and experience. 2. Thinking vs Doing If you want someone who looks busy all the time, you don't want a real data architect. Most of their time is spent thinking and reviewing. They are always trying to be ahead of the curve - ensuring things go smoothly and preventing problems. As you get higher up the data chain the work becomes more and more cerebral. A lot of companies are used to hiring technicians in data roles - then the company culture is happy to see them plugging away like worker bees. You will then be frustrated by great architects - they appear to be coasting. But, in reality, they work twice as hard - it is just less visible. 3. It Will Cost You Great data architects do not come cheaply. But, in the long run, the investment is worth every cent. They will elevate your whole data team, energize your whole team, and drive you to data excellence. Greatness starts at $250K. Remember - you get what you pay for. 4. They Are The Top Of The Pyramid Don't look to hire a data architect if your data team is just 2 or 3 people. First, you will annoy them (you are not taking data seriously), and second, you will be frustrated (they are not a Swiss army knife of data - model, analysis,m engineer, DBA). Maybe, you really need to spend your architect money on hiring smart people for each of the other roles. #data

You might want to hire for your #trading business roles like: -Data Engineers -Data Scientists -Data Architects That will mean creating a "talent pipeline". But what is a data architect? And how does he fit in this field? -A data architect is an IT professional role responsible for managing an organization’s data infrastructure -This involves designing, implementing and maintaining the technical systems that store data They serve as the backbone of an organization’s data management strategy, ensuring that data is managed efficiently and securely. Here are some of their key responsibilitieses: -Designing enterprise data management frameworks: •Data model designs •Database development standards •Implementation and management of data warehouses •Create frameworks to track data assets and their flow -Ensuring data security and compliance including: •Access restrictions •Encryption •Privacy laws -Implementing data management processes: •Data ingestion •Data transformation (related to storage) •Data storage -Build data models and strategies (not trading strategies): •Data models to identify the relationships between different data entities •Data strategies outline the organization’s approach to collecting, storing and analyzing data related to the business About the technical skills: -Proficiency in programming languages -Database management and design -Data modeling and design -Metadata management -Big data -Cloud computing Data architects and data engineers both play critical roles in the data management process, but their responsibilities and focus areas differ. One is focus on the business context and the other on the market context: A) Data architects are responsible for designing data infrastructure strategies, including: -The overall enterprise data management framework -Data security -Compliance. B) Data engineers focus on: -Building the trading system infrastructure for deployment -Maintaining the pipelines to automatize the system -Brokerage and platform's infrastructure

Are you interested in harnessing the power of Snowflake Data Warehouse? This cutting-edge cloud-based platform revolutionizes data management by offering unmatched scalability and performance. Picture it as your digital repository, where data is stored, managed, and analyzed with remarkable speed and agility. Let's illustrate with an example: Imagine you're overseeing a retail business and need to analyze sales data from various sources—online transactions, in-store purchases, and customer feedback. Snowflake allows you to seamlessly integrate these disparate datasets into a centralized repository, breaking down data silos and facilitating comprehensive analysis. Now, let's discuss career opportunities: 1. Data Engineer: Craft and implement data pipelines to ingest, transform, and load data into Snowflake. 2. Data Analyst: Extract insights from Snowflake-stored data to drive informed decision-making. 3. Business Intelligence Developer: Build interactive dashboards and reports using Snowflake data to support strategic initiatives. 4. Cloud Architect: Design scalable solutions utilizing Snowflake's cloud-native capabilities. 5. Data Scientist: Develop machine learning models and advanced analytics solutions on Snowflake data to fuel innovation. 6. Data Quality Engineer: Ensure the integrity and accuracy of data within Snowflake, maintaining high standards of data quality and reliability. In embracing Snowflake Data Warehouse, organizations not only unleash their data's potential but also create diverse career paths for data professionals. Are you ready to embark on this transformative journey? Let's connect and explore together! #Snowflake #DataWarehouse #CareerOpportunities 🚀🔥