Strategic Data Engineering Consulting: A Way to Performant SaaS Growth

Put an end to your pressing data engineering problems by getting expert support. Here’s why you may need a consultation and how data engineering consulting works at NaNLABS.

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by Matias Emiliano Alvarez Duran


The compound effect of this growth could eventually cause your systems to crash. 

According to ChartMogul’s 2023 SaaS Growth Report, SaaS businesses with an annual recurring rate of one to three million in revenue grow 192% per year. Most SaaS business growth comes from increased subscribers. This means you can go from 1000 to 2920 users in a year. 

Without the proper data engineering and architecture design, trying to scale your infrastructure can feel like putting a band-aid over a leaking pipe. 

Most businesses are caught up in daily tasks and have no room to identify or solve the root cause of issues. If this sounds relatable, you could benefit from data engineering consulting. 

In this article, we go through the different aspects of data engineering consulting, why you may need it, and how it works at NaNLABS. 

Table of contents

Get a team of experts to spot data engineering inefficiencies for you. At NaNLABS you’re not a number, that’s why we’ll craft tailor-made solutions to your data problems.

Why SaaS companies need strategic data engineering consulting 

You may need data engineering consulting to analyze one of these points:

  • Scalability and reliability. Clients often want to identify potential areas of improvement in their software to build more reliable and scalable infrastructures. This helps reduce poor performance or unresponsive service. 

  • Data integration. Growing businesses regularly need to define the best way to store and process multiple data sources. Consultancy can help identify current problems and propose alternatives by outlining the trade-offs. For instance, you may gain efficiency with a technology but see increased costs. 

  • Data security. When a business grows from an MVP to enterprise-level software, it poses new security and data compliance requirements. Consulting can help identify the biggest risks and outline a plan to fix them. 

  • Cost-efficiency. We see this often during consultancy sessions because not all of your initial technology can scale with you. Consultants can help you identify cost-saving opportunities and propose more cost-efficient technology.

  • Real-time analytics. Many SaaS businesses know that users want access to their data because it allows them to make insights—and earn money from them. So, they want to offer analytics capabilities with their products. But real-time analytics have unique data processing requirements, and consultations can determine the best way to do it. 

But consultations aren’t only useful to identify current issues. Companies may want to explore the viability of ideas or get expert advice on the best technology to use.

In short, “The point of a consultation is to reveal information that either the business wasn’t aware of or didn’t think possible,” says Gustavo Alberola, Software Developer Advocate at NaNLABS. These sessions help you tie your data engineering strategy to sustained, performant, and cost-efficient growth. 

“Consultations also warn you about future issues that might arise and you’re not seeing yet,” adds Gustavo. Thanks to the consultant’s experience, they can point out what is bound to happen. For example, potential security vulnerabilities, future crashes, or latent performance issues.

Who participates in consultations:

Usually, the person who asks for a consultation is either an engineer, a manager, or a C-level executive. The approach is different for each persona. 

Engineers usually look for specific and more detailed advice regarding their architecture or a particular technology. They look for solutions or guidance to a defined problem. They may be looking for a second opinion on the decisions they took. For example, how to build a polyglot database architecture

Managers and C-level execs, on the other hand, want more strategic advice. They are often looking to create or upgrade a product on a given budget on a deadline. They also want to understand the trade-offs of a decision they’re about to make. For instance, is it the right time to implement user-facing analytics? Can they do it with their current team?

In both cases, the questions usually revolve around: 

  • Health issues in the data pipeline and management

  • Data processing performance and efficiency

  • The performance and quality of ETL (Extract, Transform, and Load) processes

The suggestions mostly contain: 

  • Hints about current decisions and considerations to take into account

  • Hints about future problems that might arise given current circumstances

  • Suggestions about changes in architecture or technical approach to a problem

  • Links to complementary information useful to the case

During a consultation, you pay to save your time and money. Consultants anticipate future issues and prevent you from wasting resources on fixing something that could have been avoided. 

The NaNLABS way: More than just consultants

At NaNLABS, we’re Agile software developers with 10+ years of experience. Our approach to tech consultancies empowers teams by providing actionable strategies that are tightly linked to business objectives.

We’ll make sure to work alongside your team to identify the crucial problems of your operation and be completely transparent about what we find. 

But we’re more than just consultants; as your technical sidekicks, our consultants are:

  • Your partners for growth. We’re not just a vendor and you’re not a number. We collaborate with you as your strategic partners to find the most efficient solutions to your needs. However, we’ll also point out any additional information we find and be completely transparent about our findings and suggestions. 

  • Expert in SaaS businesses. We’ve worked with multiple SaaS businesses, both in B2B software development, as an augmented team, and as consultants. We have deep industry knowledge and know where to look for potential data needs.

  • Agile and results-oriented. All of our team members leave and breathe Agile. We work fast and follow a servant leadership approach. We adapt to your evolving requirements and deliver actionable results in a short period. 

Based on our experience, we work with you to spot and determine solutions to your data engineering needs. This includes cutting-edge technologies in machine learning, IoT, cloud computing, and Big Data analytics.

What to expect when working with NaNLABS for your data engineering needs

Our data engineering consulting services include three pillars:

  • Comprehensive assessments. Here we get a deep understanding of your data infrastructure and business goals.

  • Tailored roadmap. We craft a process where we explain how to make adjustments based on your strategy, goals, and budget.

  • Ongoing support. You can contact us for future questions about the suggestions we made when needed.

When you come to us for a consultation, we determine how much time we need based on your goals and data engineering struggles. During this first session, we chat about your requirements and how they tie to the business strategy. We then meet according to those findings—whether that is an hour or a three-day session. 

“The NaNLABS team worked closely with us to define the project goals and our requirements. They consistently prioritized our satisfaction and feedback to ensure that the end result met our expectations,” said Santiago Basulto, Head of Product at INE.

To give you an idea, “If the client is looking for a specific solution like an architectural design, for example, it might take 3 or 4 sessions—with back-and-forth emails,” says Gustavo. “The idea is to have a feedback loop during the design which can increase in touch points.”

The tailored roadmap is a document we produce after the consultation with all the relevant findings. Ideally, depending on the time we have together, we’ll walk you through the document and conclusions on a call. 

Then, we open up our channels for future conversation or hands-on support. And, if you need help putting the roadmap into action, we can augment your team to handle the implementation. 

Here’s a brief explanation of what goes down before, during, and after a data engineering consultation.

How we managed to conduct a comprehensive assessment of a B2B client specialized in survey satisfaction services

This client, let’s call it E-Survly, wanted us to conduct a 360-assessment of its app. We were tasked with identifying areas for improvement and optimization at the code level, data structures, and infrastructure. 

E-Survly also wanted to simplify the deployment of various environments, so we dug deep into its CI/CD workflow in GitHub. “Additionally, there were issues with Azure AD B2C configurations. Which made part of the assessment revolve around investigating this problem,” says Roberto Molina, our Full Stack Developer and Primary Consultant for E-Survly.

We had two sessions with E-Survly. During the first session, the client explained the issues they wanted to address. “The first meeting was client-driven. They explained their concerns while we listened attentively and asked the necessary questions for context. In the subsequent meet-ups, we took the lead,” explains Roberto.

The team then worked for two weeks based on the insights provided by the client, creating a document covering the entire assessment. 

This tailored roadmap summarized the conclusions of the library version reviews, project structure examination, and front-end state management analysis. “It also included database structure and seeding analysis, the review of styling methods, and a basic security assessment following OWASP Top 10,” says Roberto.

During the second meeting, the NaNLABS team presented the assessment document by focusing on the areas requested by the client. 

By the end, we came up with a list of recommendations with detailed implementation steps. We also fixed the blocking issues with Azure B2C, delivered the assessment document, and gave an estimated timeline for addressing the identified issues. “The client reviewed and appreciated the proposed plan, which led to a second consultancy phase to implement the defined work plan,” adds Roberto. 

Are you ready to unlock the full potential of your data?

You need to provide a good service to keep growing. However, you may be worried about how to process and store all of the new data inflows, on top of an already complex operation.

Whatever your needs, NaNLABS can adjust to them as your technical sidekick. Our data engineering consulting services provide tailored strategies to ensure your infrastructure is scalable, reliable, and cost-efficient. 

We help identify inefficiencies, recommend improvements, and support your team in implementing robust solutions. By partnering with us, you gain more than just consultants; you gain strategic allies committed to your growth. Our deep industry knowledge and Agile approach ensure rapid, actionable results tailored to your unique challenges. 

Need an extra pair of eyes to analyze your platform’s data engineering? Hire NaNLABS for tailored, transparent, and specific solutions to your current or arising data issues.

FAQs about data engineering consulting

  • What is data engineering consulting?

    Data engineering consulting is the practice of hiring experts to evaluate your current platform or help you solve data-specific problems. You can also hire consultants to ask questions about your ideas and explore relevant trade-offs. 

    Consultants diagnose your processes and deliver recommendations. They’re not expected to handle the implementation.

  • What happens during a consultancy session?

    Usually, during a consultancy session, the consulting party meets up with the client to understand why they hired them. The first part of the meeting is fully centered on the client. The consultants just ask clarifying questions. 

    Then, consultants take their time to analyze the business processes, libraries, and technology. Lastly, the consultants draft a document with all the findings and recommendations and present it to the client in a session. 

  • How much does a data engineering consultation cost?

    The cost for a data engineering consultation varies depending on the consultant’s experience and the client’s needs. But, prices can range from $200 to $750 per hour. 

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