SBS Creatix’s Post

The BFSI sector is leading the charge in job creation, with a robust workforce of 25 lakhs. In 2023, 1/3rd of Analytical and Data Science jobs were fueled by this industry. Stay tuned for more insights on the top skills driving this growth – Data Science, Full-stack Development, Data Analysis, Data Engineering, and Cloud Development. #TATrends #BFSIHiring #JobMarketTrends #recruitment #techhiring #PeepalInsights

If I were a hiring manager at a large company, this is what I would look for in data professionals 1️⃣ 𝐆𝐨-𝐓𝐨 𝐄𝐱𝐩𝐞𝐫𝐭: Large corporate data teams often look for people with specialized skills (e.g., Kafka, DAX, PowerBI, etc.) or domain expertise (e.g., AWS, Azure, etc.). Understand which of those skills you have and how to lean into that for different companies. 2️⃣ 𝐓𝐡𝐢𝐧𝐤 𝐎𝐫𝐠 𝐋𝐞𝐯𝐞𝐥: Large corporations deal with massive volumes of data and complex infrastructures. They want data professionals who can understand how to work in that type of complexity by designing and implement enterprise-level solutions. Showcase your experience with large, complex datasets, distributed computing frameworks, and cloud technologies 3️⃣ 𝐂𝐫𝐨𝐬𝐬-𝐓𝐞𝐚𝐦 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧: Most corporate data teams know they don’t have this and specifically look for it. Can you communicate across departments and roles? Can you bring business stakeholders on board? Do you understand the bigger data picture and business model when it comes to your role? 4️⃣ 𝐃𝐚𝐭𝐚 𝐆𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 𝐚𝐧𝐝 𝐂𝐨𝐦𝐩𝐥𝐢𝐚𝐧𝐜𝐞: Speak about being innovative, while acknowledging the strict regulatory/ governance requirements every corporate has to work within. Understand the importance of data privacy, compliance, GDPR, CCPA, etc. and highlight how you use data governance or data cleaning methods to mitigate these data risks 5️⃣ 𝐄𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞-𝐰𝐢𝐝𝐞 𝐈𝐦𝐩𝐚𝐜𝐭: Large corporations place a strong emphasis on showing your value. Demonstrate how your work would directly contribute to the company's overall objectives (research these) and showcase your organizational impact from past projects Overall, large companies want data pros who have specialization, understand the whole ecosystem, can navigate the rules, and—most importantly—make a REAL impact. What other suggestions would you have for large corporate hiring? And for that extra little bit of help, check out my newly launched resume product on Gumroad (link in comments)! Follow along for daily data, career and consulting advice by hitting the 🔔 on my profile and commenting away. #data #career #hiring #recruiting #DylanDecodes

Based on general recruitment data: 38% of people quit within the first year at a job, and 40% of this group do so within 90 days. Could be more for data engineers. A statistic on the internet says 50% of data engineers stay only 2 years or less in organizations. Some might argue with these numbers. But what if they are true? So before you dive headfirst into hiring a data engineer, take a step back and ensure you've got your fundamentals in place. Here are three key questions to ponder: 1️⃣ What are your specific data needs and goals? Are you looking to optimize your existing data infrastructure, or do you need to build one from scratch? Define your objectives clearly to align your hiring strategy with your business goals. 2️⃣ What type of data infrastructure do you have or plan to create? Every organization's data infrastructure is unique, and your data engineer needs to be equipped to handle it. Make sure your potential candidates have the skills and experience to navigate your data ecosystem effectively. 3️⃣ What's your budget and expectations for this position's return on investment? Define your budget and expectations clearly to ensure you're making a strategic hire. Consider not only the immediate impact but also the long-term value that the right candidate can bring to your organization. By answering these questions thoughtfully, you'll be better equipped to find the data engineer who in it with you for the long haul and can drive your data initiatives forward. #hiring #techrecruiting #dataengineers #hiringmanagers

Trouble #hiring #DataEngineers, Architects, and Analysts? This is a solvable problem and can be solved more reliably than a Recruiting firm. First of all- It’s not your fault. Everyone is fighting over the same low amount of supply. I saw an article last week that said for every 3 Data engineering jobs, there are only 2-2.5 Data engineers. That means some companies will be going without… THIS IS GREAT IF YOU ARE a Data engineer. BUT for CIO and CTOs who need to keep the lights on and more projects along? What if you can’t get budget from the CFO to offer a higher compensation package? Troublesome. Even more troublesome is that the Engineer you finally brought on to your team could still be headhunted for a new position weeks or months later leaving you where you were before. Using a Managed Services Provider you have an entire team of Data Engineers, DBAs, Analysts, and Architects. A good Managed Services Provider will have experts on staff and be able to take on Maintenance, Tuning, Architecture, Right-Sizing, Projects, and everything else your team needs assistance on. This way you get more expertise and can pivot more easily to projects than if you only had 1 person. BONUS: Your in-house team can sleep well at night and on vacations when the MSP handles all the after-hours emergencies. Many companies will still want to keep in-house staff, but augmenting that in-house team with an MSP? That’s a substantial winning scenario. Don’t be shy. Reach out if you are struggling to find Data Talent in this environment. #msp #partner #cio

I saw a post from #Gartner and was quite amused. The recruiter/talent acquisition is hiring a data stewardship leader with skills in data management and data governance with an experience of 10+ years. It is further intriguing when the recruiter who is hiring is having only 5+ years of experience in total. Isn't the data industry broken or am I missing something? I'm quite inquisitive on how recruitment works. Any logical responses are appreciated. #it #hiring #data #recruitment PS - And the data pipelines remain broken.

Are you hiring? Check out these profiles of candidates we are working with who are #availablenow and reach out to learn more about how they can add value to your team! #areyouhiring #toptalent

#FulltimeRole Role - Sr. Engagement Manager (Only USC And GC Holders) Location - New York City Metropolitan Area (Hybrid) Key Responsibilities: Responsible for account management, client relationships, and account growth Interacts regularly with clients to understand business requirements, define analytical problems, structure, and communicate solutions and ensure client satisfaction with strong business driving results. Working closely with BU leaders in the account development planning process to maximize the growth potential. Serves as the primary interface between senior client management and senior leadership (VPs and SVPs) Responsible for identifying and scaling pilots / POCs to a long-term transformative program leveraging latest applications of data science, data engineering, ML Engineering, and BI Developing a deep understanding of capabilities in Data, Analytics, Digital Operations and Solutions, and work with the relevant SMEs to create proposals to help drive growth Explore opportunities with current and new buying centers, support the BU throughout the deal (RFP/RFI) pursuit. Manages multiple engagements and projects with different team structures and service delivery models   Qualification: Master's degree in economics, mathematics, computer science/engineering, operations research, or related analytics areas; candidates with BA/BS degrees in the same fields from the top tier academic institutions are also welcome to apply. 12+ years of experience in the field of delivering advanced analytics-based consulting services to clients. Experience in analytics, strategy, project management, cost reduction, and business development Deep expertise in at least one of the key functional areas (such as Marketing Analytics / Customer Analytics / Supply Chain Analytics / others)  Ability to work with global teams, communicating context of the client business problem to the remote teams and effectively leveraging them in execution and owning client presentation, project management, and expectation setting The ability to communicate effectively with technical personnel as well as management/executives including verbal, formal presentation and written communication skills  Demonstrable leadership ability, superior problem solving and people management skills Close attention to detail and a commitment to accuracy Strong organizational skills and the ability to effectively prioritize in a deadline-driven atmosphere  Share resume at Smit.parmar@aloissolutions.com #AnalyticsLeadership #ConsultingExcellence #BusinessStrategy #ProjectManagement #ClientEngagement #GlobalCollaboration #MarketingAnalytics #CustomerInsights #SupplyChainOptimization #ExecutiveCommunication #LeadershipSkills #ProblemSolvingPro #TeamManagement #PrecisionAnalytics #BusinessDevelopment #TechLeadership #StrategicAnalytics #ClientSuccessStories #AnalyticsExpertise #CareerOpportunity #ProfessionalDevelopment #AdvancedAnalytics #TopTalentHiring

Hey internal recruiters, pay attention! 📣 #DataPrivacyDay is a great opportunity for us to shed some light on the distinction between a data engineer and an analytics engineer. For internal recruiters, it is crucial to understand the unique skill sets and responsibilities these roles entail. Data engineers specialize in building and maintaining the infrastructure necessary for data storage, processing, and transformation. They are experts in designing and implementing data pipelines, ensuring data quality and reliability, and optimizing data workflows. Their main goal is to enable efficient data analysis by providing a robust and scalable data foundation. On the other hand, analytics engineers focus on utilizing data to derive insights and drive decision-making. They excel in data analysis, statistical modeling, and data visualization. Their role involves extracting meaningful information from large datasets, creating reports and dashboards, and collaborating with stakeholders to identify business opportunities. When screening candidates for technical leadership positions, it's essential to consider the specific requirements of your team. Do you need someone who can design and build data infrastructure from scratch? Or would you benefit more from a candidate who can leverage existing tools and technologies to drive data-driven insights? Understanding these nuances will help you identify the right fit for your team. #data #analytics #dataday #knowyournumbers #recruiters #sql

I've helped many organisations to hire a CDO (or equivalent) and here are the things that I often have to (attempt to) course-correct 👇🏻 The reason why most organisations struggle to hire CDOs is that they have very little idea of what is possible and a misunderstanding of what a D&A function is there to do 🥹 Broadly speaking, most understand that if leveraged correctly, their data can help them drive better business performance by improved decision-making But, their perception is often that the role of the D&A team is to merely build the infrastructure, systems and tools to make the data available "The business" will do the rest, kind of mindset 🤯 And that is why, they believe the type of profile they need is a highly technical one And therefore: 👉🏻Why you see the shopping list of technologies on job descriptions 👉🏻Why most CDO roles don't "have a seat at the table" 👉🏻Why most report through a technology team (CIO/CTO) 👉🏻Why most aren't paid like their C-Suite "peers" 👉🏻The list goes on... Obviously, there are exceptions to every rule, and thankfully for the D&A community, we've seen some progress However, when it comes to why organisations aren't realising the value/benefits they expected from their D&A investment I can show you how it almost always traces back to those misconceptions and therefore incorrect hiring decisions Really, there shouldn't be a need for a JD for a CDO role.... "Help the organisation deliver value from data" would suffice - but, that equally would make for an underwhelming job description My friend James Miller posted a few weeks ago about how he identifies and describes himself as a "Commercial Data Leader" The reality is, outside of a very small number of instances, most D&A Leadership roles are commercial **Now, defining what "commercial" is, is something I see as problematic because even the most technical leader will claim they're commercial** The challenge is that most organisations just don't see it like that (D&A being commercial) They want "value" but they hire for infrastructure, systems and tools, skills/experience... That's what needs to change if we're to move the needle and start to really drive change and value from D&A #data #analytics #chiefdataofficer #hiring

If you are someone who is not working right now and looking for a Job specially in Data Engineering, then ping me telling a little bit about you. Let me see how I can help you out. I will also try my best to get you in touch with recruiters, Hiring Managers, HR's who can help you. May all of you get jobs soon! #jobs #hiring #dataengineering #bigdata