Here's how you can turn a layoff into a chance for personal and professional growth in Data Architecture.

Every end is sign of new start so layoff from one organization is a sign of new journey with new culture new tech stack and opportunity to meet with new people learn new things. Before get in to the new organization or consider new org. 1 - Consider why previous org layoff you and find gaps and fill them. 2 - Make your self updated with latest industry trends. 3 - Goto different career websites and read JD and update skills set accordingly. When you join any organization do these things. 1 - Try to find areas that are weaker find opportunities to fix them this will give edge on other existing employee 2 - Show your willingness towards new challenges

List the things that are gaps in your knowledge. Start with low-hanging fruit; things like reading a paper on a new technique. Governance - read the book DAMA - DMBOK. There may be others; this is the one I know intimately. Storage - If this is on your list, know the trade-offs between different storage techniques, things like replication and sharding. Terminology - Maybe now is a good time to understand certain terms; data hubs, meshes, fabrics; how well do you know these? How do they relate. It's difficult to deep-dive into these things when under pressure to deliver a project. For longer goals, make a plan to iterate over time. Having an understanding of where you are at in your professional career can help your personal journey.

Reflecting deeply on your forte in the data landscape, classify these into specialties and areas of growth. Ideally, you would want to brand yourself as a specialist in one or two areas where you can present yourself as a technical thought leader. Solidify those areas with certifications maybe and content contribution on social media. As for areas of growth, you can identify an area or two that would elevate your career but you don't feel super confident about them. Carve out sometime to learn and hone your technical acumen in that area. As for landing a new role, list out all potential roles in the data architecture work and give yourself a score on each role (experience, knowledge) and start applying to those that have highest score.

A layoff can be a difficult experience, but it also presents an opportunity to take control of your career path and focus on growth in Data Architecture. Here's how you can leverage your experience with Informatica and data object stores to position yourself for success: Invest in Personal Development by sharpening your skills with Data modeling/Data warehousing/Data integration tools, Explore Cloud Platforms like AWS, Azure , then maybe U can build your own brand, an Online Presence by creating a professional website or blog where you can share your data architecture knowledge&insights. Another aspect shall be to refine your Job search strategy targeting Roles: like "Data Architect," "Enterprise Data Architect," or "Cloud Data Architect."

I learned some concepts that I have been using in my work and some new concepts in data architecture these days. Abstracting and reflecting the familiar aspects help me systemize the data warehouse approaches. Learning new concepts will help future work as well.

Some things are a blessing in disguise. First, make 3 lists: 1) What you liked doing at your prior job. 2) What you did NOT like doing at your prior job. 3) What you wanted to do at your prior job but never got to. Take list #2 and throw it away. Forget you ever did those tasks. Don't put them on your resume. Take list #1 and insure that those items are reflected strongly on your resume. Take list #3 and find training, certifications, practice, groups, projects, etc. After you have some training under your belt, start listing those new skills onto your resume. You want someone to look at your resume and clearly see "Oh, here's what this person has successfully done, and here's what they want to focus on doing".

This is a good opportunity to upskill and make your knowledge relevant in your next role. Invest the time wisely in training and online courses. My recommendation are Generative AI and Data Governance. Those are relatively new hot topic where most people don't have time to explore them. Microsoft Learn is good platform to learn about Azure OpenAI service, the Azure AI Studio is very useful tool to try or built copilot application using OpenAI or other LLM.

Use this time to further your education in Data Architecture. Explore online courses, webinars, and industry certifications to stay current with the latest trends. Focus on areas like cloud data solutions, big data technologies, and machine learning to enhance your versatility. This investment in learning will make you a more attractive candidate to future employers, demonstrating your commitment to staying at the forefront of the field. By expanding your knowledge and skills, you'll be better prepared for new opportunities in Data Architecture.

Engage with LinkedIn Learning and choose one or two projects that can showcase the aggregation of your skills and knowledge. Since the technology landscape is changing so rapidly, you will have no trouble listing a half-dozen or more practical skill sets you haven't mastered, but which are adequately covered by LinkedIn Learning. I'm a highly-skilled veteran of the industry, and I used the months of layoff to complete over six different Learning Path certifications. This is a great time for you to open some cloud-based resources (Azure or Digital Ocean VMs etc..) and start architecting an application from the many free, publicly available databases out there. Success in this arena will boost your confidence for the next interview.

Contribute to the Community Open Source Projects: Contribute to open source data projects. This not only hones your skills but also showcases your expertise to potential employers. Thought Leadership: Write articles, blog posts, or whitepapers on data architecture topics. Sharing your knowledge can position you as a thought leader in the field.

You probably want to go into layoff-mode with an already-established network, rather than having to scramble after hitting the 'street'. Joining professional groups and events through LinkedIn, Facebook and X will certainly help to keep you informed. But you'll also want to rely on your own discernment and intuition when navigating the many offers to "upgrade" yourself. Since there is a lot of money in training and education these days, you may be pressured to join or support unproductive programs with unreasonable expectations. One of the simplest, effective ways to network is to write useful posts or articles on LinkedIn. This forces you to organize your wisdom, and hopefully find advocates with good feedback.

Professional Associations: Join relevant professional groups such as DAMA (Data Management Association) to connect with other data professionals. Networking Events: Attend industry conferences, webinars, and meetups to build connections and learn from peers.

This effort truly fits into the maxim "you don't find them, they find you..". Some professionals claim that a brief, one-pager is the way to go, while other seasoned recruiters insist that a comprehensive, detailed account (5+ pages?) is the only way to impress. I ran with both versions and found that the longer, detailed account was the only one getting attention. And it kept getting longer as recruiters insisted that I include some other detail relevant to the current position. Upload your resume to Dice, Indeed, Monster and other job boards - along with a carefully written profile. Its a good idea to change your resume weekly. This helps to ensure that it remains near the top when recruiters download "new" resumes as they often do.

This is the one thing which would be relevant, in any IT professional career. Stay updated and keep learning new things. And you can find opportunities in bad situation to start with. It is not easy but atleast one could try.

The hours invested in your career should actually increase when you are between jobs. This is because you are applying to positions every day in addition to training/development and the exercise of your skills in personal projects or course work. The advantage here is that you can now invest more time in mastering theory and new skills without the burden of scheduled meetings, report deadlines and other administrative efforts that accompany any job. For example, I needed to be laid off in 2014 in order to master GIS and related database skill sets which became a critical part of subsequent positions. Working with a certain well-known open-source, I found and reported some data deficiencies. They never thanked me, but they made the changes!

Many possibilities are there to practice skills online and trial tools. Hands-on experience gets more confidence. In my experience, I noticed when I learn tools and/or concepts, I got opportunities to explore them more. Practicing skills get an opportunity to learn practical challenges, than theoretical learning.

Bridging Theory and Reality in Data Challenges. Theoretical knowledge lays the groundwork, but real-world scenarios introduce complexity. Practical experience bridges this gap by enabling you to apply theory to actual data challenges. Whether you’re crafting a database schema, fine-tuning ETL workflows, or ensuring robust data governance, hands-on work reveals nuances that textbooks often miss.

Take that time to analyze some aspects to strengthen, if a new professional approach is necessary or if it is the same focus, ask yourself: What other aspect should you introduce to be differentiating in what you know how to do with data? Transmit what differentiates you to those who are interested in having your services. I believe that this is as important as the experiences gained and the professional success stories that have been harvested. Showing reinvention is of great help.

Layoffs are tough and can be stressful. But remember nothing is permanent and this too shall pass. Instead you taking it negatively, utilize your time and energy to channelize it to make things happen. You can definitely think big and clear and think of it as an opportunity to make things much better for yourself. Focus on physical and mental health. One can achieve great results by positively working towards it.

Even when faced with seemingly insurmountable challenges and intricate situations, we must persevere with unwavering determination, taking one step at a time. It is crucial to remember that data architecture is the cornerstone of our work, and the experiences gained in this field, even in the realms of reality and the physical world, empower us to overcome any obstacle with greater ease.

Upskill and Reskill: Take online courses in machine learning. Get certified in AWS or Azure. Networking: Join LinkedIn groups for data engineers. Example: Attend virtual meetups or webinars in your field. Freelance or Contract Work: Look for freelance projects on platforms like Upwork. Example: Complete a project analyzing sales data for a small business. Update Your Resume and Portfolio: Add recent projects and skills to your resume. Example: Highlight a recent project where you optimized a data pipeline. Build Your Personal Brand: Share your knowledge and projects online. Example: Write blog posts about data engineering, contribute to forums, and share your projects on GitHub.

Retrenchment destroys your self-confidence, there is no way around this. You have to first fix your mental state before you start upskilling; there is a perfect role for you with the knowledge you already have, but you first have to fix your mental state. Use mental frameworks like "Habits of highly efficient people" to start believing in your capabilities again, the rest will sort itself out.

Begin by reflecting on your career achievements and identifying areas for improvement. Use this time to upskill through online courses, certifications, and attending industry conferences to stay updated with the latest technologies and trends. Expand your professional network by joining relevant forums, LinkedIn groups, and connecting with former colleagues. Consider freelance or contract work to gain diverse experience. Additionally, leverage this period to work on personal projects or contribute to open-source initiatives, showcasing your expertise and passion for the field.