In this article, we’re going to look at some of the ways organizations like yours can utilize Snowflake Data Engineers to get maximum value from your Snowflake implementation and explore some cost-effective ways for finding these SnowPros for your team.
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More and more organizations are adopting Snowflake. And small wonder. In an AI and data-first world, Snowflake offers its users unique architecture that helps them handle and host large volumes of data more efficiently. Usage of the solution is exploding, with Snowflake’s TAM expected to balloon to $290B by 2027 at a 5-year CAGR of +15.7%.
But like any smart piece of kit, Snowflake isn’t a silver bullet. Getting the most out of your Snowflake implementation requires careful planning and ongoing due diligence, which only a qualified Snowflake Data Engineer can ensure. So, having these specialists on your team for the long-haul is crucial for maintaining a competitive advantage, optimizing costs, ensuring data quality and compliance, scaling efficiently, fostering collaboration, and driving revenue growth for your business.
Let’s delve deeper into some of the specifics of how a Snowflake Data Engineer can help you make the most of the Snowflake platform, and where to find delivery-ready talent who will stay with your organization long-term (without breaking the bank).
1. Ensuring effective real-time data ingestion
Effective data ingestion plays a big part in maximizing the ROI of your Snowflake integration. The more efficiently you can bring data into Snowflake from various sources, the better the platform will be at enabling business intelligence.
While Snowflake’s batch data ingestion is powerful, your team should really be leaning into Snowflake’s real-time ingestion to minimize latency. Snowflake supports real-time data ingestion through its Snowpipe service (familiar to most SnowPros), which allows users to continuously upload new data as soon as it’s available. By using real-time data ingestion, you can ensure that any business decisions you make are based on the most current data sets.
Snowpipe can be used alongside popular cloud storage services like AWS S3, Google Cloud Storage, or Azure Blob Storage to automate and streamline the ingestion process, giving you plenty of options when implementing real-time ingestion.
What that means in practice is that your enterprise can securely share data with your partners across the globe on any of the three major clouds without the time-consuming process of generating APIs and/or files, saving you time and streamlining your operations.
On top of this, a Snowflake Data Engineer can set up relevant Snowflake alerts to warn of any data quality issues before they spiral into a costly data fix, eating into your budget.
2. Leveraging Snowflake's unique features
To get the most value out of Snowflake, you should be utilizing its full range of unique features and capabilities. Many of these features (like its architecture, scalability, and performance-enhancing features) will go a long way towards helping you use the platform most efficiently, maximizing its return. Consequently, having a certified SnowPro on your team will ensure that you’re making the most of these powerful features, some of which we’ve listed below.
Multi-cluster shared data architecture
Snowflake’s multi-cluster shared data architecture splits up storage and compute resources, allowing each group to scale independently. This means that you can handle dynamic workloads efficiently and cost-effectively. During peak usage times, your Data Engineers can spin up additional compute clusters to maintain performance without impacting the overall cost structure.
Time Travel and Cloning
Snowflake’s Time Travel feature allows you easy access to your historical data, enabling you to perform point-in-time recovery of tables, schemas, and databases. This feature can be invaluable when it comes to auditing, troubleshooting, and data recovery tasks where you need to look back over the data you’ve ingested and processed over time.
Cloning, on the other hand, allows you to create zero-copy clones of data, enabling rapid environment setup for development and testing without incurring additional storage costs that bump up your operational overheads.
Data governance, security, and sharing
Snowflake’s data platform enhances traditional data governance with capabilities for data classification, data tagging, dynamic data masking, as well as row access policies. Snowflake also has a secure data-sharing capability that means organizations like yours can share live data with external partners, without the need for complex Extract, Load, Transform (ELT) processes or data duplication.
This feature will massively enhance your collaboration, improve supply chain efficiency, and open new revenue streams by monetizing your data assets; all of which can help drive a better ROI from your Snowflake implementation.
What’s more, Snowflake’s data platform has marketplace app-style connectivity to over 100 partners, which only a qualified Data Engineer with the right tech knowledge and hard skills (that extend well beyond Snowflake certifications to coding, data modeling, and extensive cloud vendor knowledge), plus prior industry experience, would know how to use to their fullest potential.
3. Staying on the cutting edge of Snowflake, data, and AI developments
With a product as rapidly evolving as Snowflake, and in an era where groundbreaking AI advancements are taking place almost every day, it’s crucial to have an expert on your team who can keep an eye on the latest tools and trends, understand them, and assess which features you should adapt for your specific Snowflake implementation.
For instance, new LLM capabilities within the Snowflake data platform can now enable the translation of text into different languages, summarization of text, sentiment analysis, and extraction of answers to questions based on your data.
Furthermore, Snowflake’s data platform also contains Streamlit, which enables interactive dashboards with a minimal amount of code. Last but not least, Snowflake now allows for the creation of data applications within Snowpark. These applications can be written in Python, Java, JavaScript, Scala, and SQL, so you need Data Engineers with solid programming skills, as well as a passion for staying up to date with Snowflake and AI, to make the most of these.
A Snowflake talent solution that boosts your ROI
As you can see from the reasons we’ve listed above, a qualified Snowflake Data Engineer with the right transferable skills and industry experience can help you drive maximum value from your Snowflake implementation, reducing running costs and boosting the return you can generate by better managing your precious data assets.
But with the demand for Snowflake on the rise, finding Data Engineers who are both skilled and affordable, and will not be poached after a few months in their role in a fiercely competitive job market, can be extremely hard.
Traditionally, organizations that use Snowflake have relied on consulting companies to find these in-demand specialists. However, these consultancies will often take a large proportion of your ROI for themselves, in exchange for their services.
At Revolent, however, we can help you build and train your trusted team of experts who can help you utilize Snowflake’s data platform to the fullest without breaking the bank. With our Snowflake Talent Creation Program, you can access certified Data Engineers who can significantly boost the ROI of your Snowflake platform at a fraction of the cost that traditional consultancies would charge.
In fact, we’re actively working with Snowflake to help create the talent needed to support its ambitious growth target of adding 6,000 SnowPro-certified individuals to the ecosystem over the next year. These specialists can be deployed to organizations just like yours, equipped with expert knowledge that extends well beyond Snowflake certifications, ready to make an impact from day one.
What’s more, our talent program can be fully tailored to meet your business needs—all you need to do is sit back and let us handle the heavy lifting, from hiring and onboarding industry specialists, to training and deploying them, to investing in their ongoing development.
