If you have an existing Snowflake implementation, this article will talk you through the benefits of having a certified Snowflake Data Engineer on your team. As the leading tech talent and creation experts, we’ll also share our Snowflake Data Engineer hiring tips to ensure you select the right specialist for your organization. So, let’s dive in…
Use the jump links below to navigate to the section you're most interested in:
- The growing need for Data Engineers
- Benefit #1: In-depth Snowflake expertise
- Benefit #2: Valuable Data Engineering skills
- Benefit #3: Support for your AI and ML initiatives
- Top skills to look for in a Snowflake Data Engineer
- Sizing up Snowflake Data Engineer skills
- How to access Snowflake talent the easy way
The growing need for Data Engineers
Today, there’s more data at our fingertips than ever before, creating massive opportunities for businesses like yours to gain a deeper understanding of their operations, their customers, and the markets they work in.
We all know how much of a priceless resource our data is, but in reality, collecting data and extracting value from it are two very different things.
Businesses are becoming increasingly aware of how important good data management is if you want to derive accurate, actionable insights from your data. And it’s this awareness that’s driving a huge surge in demand for data management software and services.
Organizations are becoming ever-more reliant on data to inform their decisions, especially as the role of AI in business is rapidly expanding. This process is built on mammoth quantities of data from a huge range of sources, including social media, IoT devices, sensors, and customer interactions. Making the most of this data requires robust DBMS software that can properly store, organize, and analyze large amounts of information and support data-driven decision-making.
As the need for such products explodes, the market for Database Management System (DBMS) software is on track to more than double by 2027. One of the products leading this phenomenal growth is the Snowflake platform, which is set to grow its total addressable market from $140 billion in 2022 to a massive $290 billion over the next three years.
If you’re implementing Snowflake Data Cloud, having a data expert on your team can help you manage, analyze, and utilize your data much more effectively.
One role that’s becoming increasingly popular among Snowflake users is the Snowflake Data Engineer. Tasked with overseeing the implementation and maintenance of data solutions using Snowflake’s Data Cloud, Snowflake Data Engineers play a crucial role in building and optimizing data pipelines, designing data models, and ensuring the efficient processing and analysis of data within the Snowflake platform.
Why your organization needs a Snowflake Data Engineer
If your business is looking to extract real value from its data, having a Snowflake Data Engineer on your team can give you a huge advantage. A good Snowflake Data Engineer can help your organization harness the power of data and AI technologies to drive growth, innovation, and competitiveness in a market where everyone is leveraging AI to get ahead.
Here are a few things that a Data Engineer can bring to the table.
Benefit #1:
In-depth Snowflake expertise
Snowflake is a massively useful platform with a huge range of functionality ranging from data storage and SQL-based query processing to complex analytics. But no matter how smart the product itself is, data management is a complex task, and getting it right requires someone at the helm with in-depth knowledge of Snowflake, its functionality, and how its use cases can be applied in your business.
An experienced Snowflake Data Engineer will understand how to leverage the full potential of Snowflake’s features and capabilities to manage and analyze your structured, semi-structured, real-time, and batch data most effectively.
Benefit #2:
Valuable data engineering skills
As well as having an understanding of the Snowflake platform itself, Snowflake Data Engineers come with a multitude of additional skills that can be a real advantage for your business.
As Snowflake experts, they’ll likely wield excellent SQL skills, for example, which allow them to navigate, manage, and manipulate complex datasets.
Other data engineering skills like data modeling, ETL (extract, transform, load) processes, data warehousing, and data integration are essential for organizations seeking to build and maintain robust data infrastructure that supports ambitious data-related goals.
In addition, our program equips Snowflake talent who possess prior relevant industry experience with dbt and SnowPro certifications, as well as additional skills on in-demand technologies, such as Fivetran, Apache Airflow, and Streamlit.
Benefit #3:
Support for your AI and ML initiatives
With everyone and (and their dog!) adopting AI and machine learning (ML) technologies these days, businesses like yours need to be on the lookout for implementing intelligent, automated technologies and solutions that help you anticipate the demands of your markets and help you operate more efficiently.
But before organizations can develop their own AI and ML solutions, they need a strong foundation of data on which to build it on. To fully capitalize on the opportunity that AI and ML offer, your business needs Data Engineers who can design and implement the data pipelines that will help train and deploy ML models.
By planning and building effective data infrastructure, Snowflake Data Engineers play a crucial role in laying the groundwork needed to support AI and ML projects and create accurate and productive AI solutions.
Top skills to look for in a Data Engineer
The best Snowflake Data Engineers will have a crucial combination of technical skills and soft skills, as well as in-demand certifications like SnowPro and dbt, that enable them to effectively work not only with data but also with the rest of the business.
Here are some key skills to look for when you’re hiring a Snowflake Data Engineer.
Technical skills
- Snowflake expertise
Candidates should have a strong understanding of the Snowflake platform, including how to model and warehouse data, how to query data using SQL, and how to optimize the product’s performance.
- Data engineering skills
Candidates should also be proficient with wider data engineering skills like ETL processes, data integration, data pipelines, and data transformation.
- Programming skills
Programming skills in languages like Python, Java, or Scala are important to look out for too, as they’ll allow candidates to build data pipelines, automate tasks, and integrate data with other systems. Database management
Experience with other database technologies like SQL Server, MySQL, or PostgreSQL can be really beneficial, and show that candidates have a well-rounded understanding of database management principles and best practices.
Soft skills
- Analytical thinking
Snowflake Data Engineers need to have strong analytical skills to understand complex data requirements, identify patterns and trends, and derive useful insights from data.
- Problem-solving
Candidates should be able to troubleshoot any issues that might crop up with Snowflake, as well as optimize queries and find solutions to technical challenges that your business may face during data engineering projects. - Communication and collaboration
Data management impacts the entire business, so effective communication skills are crucial for collaborating with team members and presenting insights to stakeholders. Translating highly technical concepts into more accessible language and being able to work with colleagues from different backgrounds and disciplines will help Data Engineers thrive in their roles.
Sizing up Snowflake Data Engineer skills
If you think you’ve found a great potential Snowflake Data Engineer for your team, you might be wondering how best to make sure they have all the qualities you need. There are many ways you can assess a candidate’s skills throughout the interview stage—the best option is usually a combination of these techniques, which will help you get a well-rounded view of your candidate and their expertise.
Technical assessments
Use technical assessments or coding challenges to evaluate candidates’ knowledge of Snowflake, SQL querying, and other programming skills.
Previous projects
Go through a candidate’s portfolio and ask them to walk you through real-world data engineering projects they’ve worked on, so you can see how they’ve applied their skills during other projects. Getting them to outline the challenges they faced, the solutions they implemented, and the outcomes achieved not only shows you their technical skills but also gives you an idea of how they work under pressure.
Certification review
Check out the candidate’s certifications. Do they have anything in database management or data engineering? What kind of Snowflake-specific certifications have they earned? Look out for the SnowPro (Snowflake’s official accreditations) Core certification and the SnowPro Advanced: Data Engineer certification in particular.
SnowPro certifications might even help boost your team’s productivity: according to research, 34% of Snowflake professionals saw more efficient work deliverables, resulting from increased depth of knowledge and greater job performance, after earning a SnowPro certification.
By evaluating both hard technical skills and soft skills during the hiring process, businesses can identify qualified Snowflake Data Engineers who possess the technical expertise and interpersonal skills necessary to excel in data engineering roles and contribute to the organization’s success.
How to access Snowflake talent the easy way
Looking for Snowflake talent to support your organization’s data goals? You’re in the right place.
As a member of the Snowflake Partner Network, we can help you access the talent you need while reducing your recruitment, onboarding, and training costs.
From recruitment and training to onboarding and continued professional development, we handle the entire process, delivering the Snowflake and dbt-certified Data Engineers you need on your team with ease, with zero capital investment.
Built in collaboration with Snowflake, our talent program can be fully tailored to meet your business needs and project demands.
Win and deliver more projects with certified Data Engineers on your team!
