When many people think of working with data, languages and tools like Python, Apache Spark and NoSQL databases may come to mind. And considering how highly technical data roles are, these types of technologies are undoubtedly important.
Yet, according to Tom Parker, hard skills are just a fraction of what data teams should look for when searching for new talent. As director of data at offline marketing agency Share Local Media, Parker knows firsthand what goes into building out a data team.
While Parker believes there are many different attributes that define effective data teams, such as strong communication skills and the ability to anticipate future roadblocks, there is one element in particular he considers crucial for successful growth. In his mind, data teams should zero in less on solving technical problems and more on how their work will affect the business as a whole.
“During every technical decision, the focus should be on what additional business value this will yield for the wider organization, which should guide decisions around which projects to undertake and how to implement them,” Parker said.
Built In NYC caught up with Parker to learn what strategies and skills enable data teams to scale successfully and uncover the most important lessons he’s learned while growing his team.
When it comes to scaling your data team, what are the most important personnel and hiring considerations?
Most roles on a data team are inherently technical and will have prerequisite competencies with coding languages, software packages and platforms. During the hiring process for these roles, it’s natural to focus primarily on these hard skills. Yet when searching for the best candidates to join your team, it’s important to consider the full range of skills that make a data team effective. Finding candidates with great technical skills should be the baseline of the hiring funnel, not the goal.
Deciding which attributes make an ideal candidate requires understanding the function and needs of the specific role you are hiring for. Beyond technical expertise, most roles require some level of problem-solving ability and competence in distilling a business problem into a technical exercise. Few roles are purely individual, so it’s important to have strong communication and collaboration skills. Many data team members will regularly work with business-side teams or clients, which is why clear and straightforward communication is crucial.
On the technical side, what steps have you taken to make sure your tools, systems, processes, workflows, and more are set up to scale successfully alongside your team?
In all decisions surrounding tools and processes, the central consideration must always be: What is the aim of these tools or processes in serving the needs of the business, and how should they be improved to better meet those needs and anticipate changes as the business and data team scales?
As a data team grows, it’s likely the team will identify many potential tools and process changes that could improve the workflow. One of the biggest challenges is prioritizing what may be conflicting initiatives in light of limited resources, which requires a careful balancing of near-term benefits and long-term strategic value. General areas for development may include data architecture, storage and management, automating and standardizing manual or ad-hoc processes, and communication and workflow management. Any change to data team processes will bring certain costs and disruption, which will need to be considered when planning the data development roadmap. The success of these initiatives, particularly those that involve the deliverables for business teams and clients, will hinge on how well you can account and prepare for this disruption.
Finding candidates with great technical skills should be the baseline of the hiring funnel, not the goal.”
What’s the most important lesson you’ve learned as you’ve scaled your data team, and how do you continue to apply it to your work?
As our data team has grown, the most important lesson I’ve learned is to consider the role the data team plays within the larger organization during every strategic decision. It’s insufficient to focus only on the technical problem in front of you.
Decisions regarding internal changes to the data team should be guided by the pursuit of delivering better value to the business, whether those changes are about improving existing workflows or developing new capabilities or products. It’s also crucial to understand that the data team doesn’t function in isolation and must often work in close partnership with business units. By acknowledging this, the team can ensure they’re tackling the right problems and that there is business-side buy-in for process changes brought forth by the data team.
