Today, organisations across every sector are gathering huge amounts of data from their consumers. But many businesses struggle to effectively leverage this data to drive business decisions. This is usually because of a knowledge and skillsets gap within the team.

As businesses begin to recognise the value of data early on, hiring your first Data Engineer to make sense of it all becomes a crucial step towards strengthening your technology function. For start-ups without a dedicated internal talent team or a network of contacts to lean into, finding that first hire can take up valuable time and resource that’s better spent elsewhere.

Burns Sheehan have successfully placed the first Data Engineers for multiple clients across SaaS and Consumer Tech industries. We've pulled together some of the key considerations drawing from our own experience, to help you navigate when the right time is to make your first data hire, and the core skills to be looking for.

When’s the right time to hire a Data Engineer?

A common challenge we come across with clients is when they’re accumulating lots of unstructured data from multiple channels, stored across multiple platforms. Hiring a Data Engineer becomes essential when you need someone to make sense of this data and transform it into consistent and reliable information to inform strategic decisions.

This requires creating a single source of truth and ensuring that your data is unified and accurate. While the specific triggers and use cases will vary across industries, here are some common scenarios where a Data Engineer can make a significant impact:

  • SaaS Products: Using data to inform product or commercial decisions such as price optimisation, supply chain optimisation, or resource allocation.
  • E-commerce: Enhancing customer experiences through personalisation, ad targeting, and customer loyalty programmes.
  • HealthTech and FinTech: Ensuring the highest security standards for customer data, optimising operational efficiency, and managing risk effectively.

 

Analytics Engineer vs. Data Engineer – Which do you need?

Deciding between hiring an Analytics Engineer or a Data Engineer depends on your business priorities and what you need your data for.

  • Data Engineer: If you’re a high-traffic start-up and the success of your product relies on scalability, then a Data Engineer is essential. They focus on building and maintaining the infrastructure required to collect, store, and analyse data efficiently.
  • Average Salary for a Series B Org in London: £70,000 - £100,000

  • Analytics Engineer: If you need someone to help analyse data and generate insights without the heavy infrastructure focus, an Analytics Engineer can be a good fit. They often have skills in self-service analytics and can grow with your company.
  • Average Salary for a Series B Org in London: £60,000 - £90,000

 

Core skills for your first Data hire

Your first data hire isn't just about technical expertise. It's about finding someone who can communicate effectively across teams and departments, manage multiple stakeholders from CTOs to marketing and sales, and lay a solid foundation for your data function. 

Data Engineer:

  • Proficiency in data engineering programming, Terraform / Infrastructure-as-code, Python, SQL, and cloud platforms – it’s likely your first Data Engineer will need to set up the whole data infrastructure, so this tech stack is a good base of skills. Visualisation skills are a bonus, but Python and SQL skills are essential.
  • Experience in building and maintaining data pipelines (e.g., Spark/PySpark).
  • Using orchestration tools like Airflow or Luigi, and data warehousing or data lake capabilities (e.g., Redshift, S3, Snowflake, Big Query, ADF/Gen 2).
  • Familiarity with data warehousing solutions and ETL & ELT processes.

Analytics Engineer:

  • SQL, DBT, data visualisation software, cloud are the typical core skills - (Python is needed to a lesser extent than a Data Engineer)

A typical profile for your first data hire would include:

  • Experience: Expect a senior candidate with 2-3 years of experience in a senior role. You’re looking for someone who has experience in a standalone role or a small team where they significantly contributed to the development of the data ecosystem. Look for candidates who can discuss their impact on organising the data warehouse (or similar) and establishing a single source of truth for both basic and advanced analytics. Candidates with experience managing budgets, particularly cloud costs, are a huge bonus but will be hard to find.

  • Motivations: Look for someone interested in working on exciting greenfield projects, ambitious, and potentially aspiring to a head of data role in the future. Being the first hire brings opportunities to progress in a company quickly, so look for someone with leadership qualities who can be a person of influence within the company.

  • Communication: Someone who can talk and educate others, managing stakeholder expectations and interfacing with different departments effectively. Don’t overlook personality. This person must be a strong communicator and understand both the technical and commercial reasons behind their work.

 

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A good first hire in a Data Engineering team should exhibit several key qualities to effectively support and drive the team's growth and success, but the four key skills for me are:

  • Growth Mindset: Ability to stay updated with new and emerging technologies, ensuring continuous improvement and relevance in the rapidly evolving field of data engineering.

  • Business Value Focus: Someone that's deeply connected with the organisation’s goals in order to prioritise projects that significantly benefit the company. Aligning work with key objectives for maximum impact rather than getting lost in the technical details.

  • Technical Foundation: Knowledge to select the right technologies and tools to build a scalable, flexible platform with self-serve capabilities, empowering teams to independently access and utilise data.

  • Effective Communication: The ability to convey complex technical concepts to non-technical stakeholders across different departments, and maintain a bias for action to ensure quick progress and continuous improvement in a fast-paced environment.

- Martin Grayson, Senior Engineering Manager @ comparethemarket.com

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If after reading this you think it’s time to make that first data hire, reach out our Head of Data Nick Wright, who’ll help you define the role and find the perfect fit for your team. With an extensive network of data professionals across the UK and Europe, we're confident we can connect you with the right talent to build a strong data function and drive your organisation forward.