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Unlock the secrets to hiring and retaining top-tier Data Warehouse Developers! With a staggering 21% job growth rate projected by 2028, the demand for these tech wizards is soaring. Dive into our blog to discover how to navigate this talent surge and keep your data game strong! https://buff.ly/3TRoxbA

🚀 SQL Time 🚀 Imagine you're managing an Employee database for a tech company. Your task is to generate a report on high-salary employees with specific job titles. The goal is to order the employees first by their roles and then by their salary within each department. You need to retrieve employee details, including their IDs, job titles (specifically 'Software Engineer' and 'Data Scientist'), hire date, and salaries from the Payment table. #sql #database

 list of essential functions and concepts one must know as a Data Engineer or Dat Analyst or Data Scientist: 1. SELECT 2. FROM 3. WHERE 4. HAVING 5. ORDER BY 6. GROUP BY 7. COUNT/COUNT DISTINCT 8. Aggregations (AVG, SUM, etc.) 9. JOINs (INNER, LEFT RIGHT, OUTER, SELF and CROSS) 10. CASE statements 11. LIKE/ILIKE 12. Window Functions (LAG, ROW NUMBER(), RANK, etc.) 13. IN 14. UNION Advanced SQL 15. CTEs 16. Subqueries 💻 From querying databases to optimizing data manipulation, these functions are the building blocks of SQL proficiency. What would I add to this list? Let's code our way to success! #SQL #DataAnalytics #ProgrammingJourney"

Hi all, Today working on Data Scientist, San Jose, CA (Onsite) Detailed JD: Contractor is expected to support a range of activities associated with dashboarding and analytics.   The nature of the work tends to fall into two categories 1) complementary detailed analytical and/or critical documentation development work supporting an inflight project or 2)deliver against ad hoc requests that are dashboarding / metric build out related Monthly deliverables include: ● Expanding access permissions: a system for managing users, groups, and memberships for the purpose of access control. ● Dashboard/Metric development.   Additional Services Include:   ● Validate data integrity and maintain projects, action items, checklists, and or issues data attributes within client’s tool ecosystem ● Lead and coordinate weekly vetting of incoming new capability requests. ● Support and coordinate monthly roadmap review. ● Generate ad-hoc reports analysis. ● Provide readouts of project status to stakeholders; and ● Weekly progress reports detailing progress of deliverables. kindly provide me resume :narendra.kumar@symphonyenterprises.com

Data Analyst vs. Developer: Which Tech Career is Right for You? Please Like, Share , Comment and Subscribe for more videos

Hiring for one of my friends company: Data scientist/analyst Contract role, hybrid Location: Poland/Berlin/Germany #polandjobs #berlinjobs #germanyjobs 1. Finding data issues in terms of governance. finding data that is missing from our clean layer that needs to be updated. detecting areas for improvement/recommendations in terms of data models. cooperating with data science on our install intelligence team to help research any issues they find. 2. Developing an anomaly detection model for our data sets. basically, high level idea would be to help us develop a set of analytics that we can alert off of to proactively detect issues. items like 7 day avg, std-deviation, IQR to better understand our datasets and how they generally behave. once that is complete, develop a more sophisticated model for running detections at 30 minute intervals (or as quickly as we can which makes sense from a cost perspective). Send me the CVs to srinikadiri@yahoo.com

Am I a data engineer or a fire fighter 🧘🏿 Day in the life of a Data Engineer includes 1. No matter how much work you close before the weekend, new day new problems 🎁 2. Develop queries ⌨️ 3. Share sample data for data sanity with source and business teams 💾 4. Day to day project related issues and solutions 🪛 5. Ensure all data pipelines are in place and data reaches designated teams to avoid escalation 🆘 6. Take some help from colleagues, senior management or business teams to not get stuck over a problem 🚒 7. Work on compliance, yes, that's a routine 🌇🌃 If that sounds cool, get your hands dirty. #data #dataengineering #banking #engineering #growth #workexperience

📈 Vacancy Tracker (UK) 📉 Significant rises in job openings for technical roles for the period of 27th May - 26th June (LinkedIn). 🔺Machine Learning Engineer - 666 ➡ 961 🔺Data Scientist - 760 ➡ 912 🔺Data Engineer - 2,122 ➡ 2,389 Slight decline in the senior-level vacancies which is pretty indicative of what we're seeing of companies prioritising hiring in roles that directly contribute to immediate revenue generation or cost efficiency over expanding high-cost executive roles. 🔻 CTO - 264 ➡ 216 🔻Head of Data Science - 39 ➡ 26 📞 Let’s talk market trends #VacancyTracker

One of the pain-points I heard from data leaders last year was that it can be hard to justify hiring a data engineer. Hiring a data scientist or analyst is generally easier to sell to the business because their work is immediately tangible. Many data scientists and analysts are also great at building SQL and notebooks workflows that can take data from Data Lakes and process it into a usable format. So why even hire data engineers? This is a question so many companies have run into. The truth is, companies can get away without data engineers for a little bit. But here’s what often happens. 1)Tech-debt starts to build 2) Lots of pipelines and data workflows get set-up for one-off requests 3) No one ever thinks about data governance 4) Even small changes risk breaking multiple critical flows 5) No one wants to own any of the above This has happened time and time again. It eventually comes to a head once the CEO is tired of dealing with conflicting numbers, slow dashboards and the constant "we can't change that, or something might break" responses. If you're that CEO or a data leader who needs to have that conversation with the CEO, then let's talk!