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Managing and Running Large Engineering Teams Successfully

Federico Fregosi

Principal Consultant - AI & ML Practice at OpsGuru

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Fast Growth Within Teams

The engineering team that Iā€™m currently working with is made up of 177 engineers. Weā€™ve been through a growth phase in the past year, which has involved implementing many new processes. Building and scaling a team is commonly discussed, but Iā€™ve found that running a team of this size is often overlooked.

I want to focus on how to scale and run an engineering management function of a team of significant size. When youā€™re getting there, the role is way less about engineering strategy and the key aspects, for me, are developer productivity, learning and development, inclusivity, HR, talent. You end up having a larger strategic focus on operational processes.

Tools to Manage a Large Team

Getting Comfortable with Numbers:

Iā€™ve been working with teams of different sizes for most of my career. Iā€™ve learned that the largest change when moving from a small/medium-sized team to a team where you stop knowing everybody is that you have to start reasoning with numbers and metrics.

On a small team, itā€™s easy to say, ā€œI have four engineers on this project and three on another.ā€ Thatā€™s all gone when transitioning to a larger team ā€“ percentages take over. As an engineering director or VP of engineering, itā€™s difficult to look at specific team members and nearly impossible to have a day-to-day connection with them. Thatā€™s where percentages come into play, where leaders can assess change within a team.

Assessing a Teamā€™s Health:

When working with larger teams, the option to provide win-win solutions that mitigate challenges and make everyone happy is gone. I know that whatever change I implement, some team members will be happy while others will not be. The trick is to reduce the number of people that are unhappy by assessing the team before and after.

Thatā€™s where getting to know the team comes in handy. With small teams, itā€™s easy to talk with everyone in the team ā€“ it changes as the team grows, however. There needs to be correct policies and processes in place to evaluate the teamā€™s health. Even the common ā€œskip-levelā€ meetings start being almost impossible at a certain size.

My current company has an innovative way to assess the status of the team. We have tools that integrate with Slack and, on a weekly basis, ask all of our team members to share how they feel ā€“ about the company, their performance, their manager, and their workā€”asking these questions and monitoring the responses in incredibly important to evaluate the status of the team.

In the big picture, when leaders transition to managing large teams, they need to focus on company-wide strategy at a high level. Rather than asking each team how they feel or even each manager or director, leaders need to set up the process to do this ā€“ like the survey in my company.

Looking at the Right Metrics:

As growth continues and metrics become increasingly important, people may look at the wrong metrics. For example, typically assessing engineer satisfaction is done by looking at engineer retention. If people are not leaving, they must be happy with their role. I think itā€™s more complicated than this, however ā€“ as this metric forgets compensation and specific circumstances.

Instead of using retention, I use ENPS (Employee Net Promoter Score), which involves weekly check-ins. In addition, I look at the number of referrals team members are providing ā€“ as our company has a significant bonus for referring a candidate. Looking at the two of these, I can see a clear correlation between referrals and employee satisfaction.

There should be three levels of metrics: individual, team, and organizational. Different metrics are made for different levels, and ideally, looking at them on these different dimensions will add insight for leaders.

Creating a Narrative:

As Iā€™ve moved into a VP role, Iā€™ve become further removed from the ICs I work with. Itā€™s impossible to motivate each engineer individually, meaning Iā€™ve had to implement a narrative thatā€™s inspiring on an organizational level. Itā€™s not just about finding the right motivation strategy but ensuring that it is well communicated and understood by the teams. Really, thereā€™s no such thing as ā€œovercommunicatingā€.

Learning and Development:

At the beginning of my career, I wanted my team to act as a career accelerant for individuals. I wanted the people I worked with to take full ownership of their roles ā€“ in turn allowing them to feel empowered by the accountability. As Iā€™ve grown to become more senior, Iā€™ve realized that this formula works well in very ā€œmission-ledā€ companies that tend to attract a certain profile of individuals but fail in different, more established, settings. Iā€™ve shifted my focus to ensuring that my company creates the right environment, to encourage people to operate in this mindset, rather than expecting them to be naturally driven towards it.

A strong component of this is L&D. Not only do I allocate funds for professional development, but I also set aside time for my team to focus on development. In a company setting, we need to ensure that whatever teams are spending their time on is upskilling their skills while connecting with the business goal of the organization.

Engineering Career Frame:

Once organizations get to a certain size, one thing Iā€™ve noticed is that it is hard to standardize the seniority of roles for promotion. Especially if it has not been done at the beginning, as common in startups of all sizes. My company tries to do this in a few different ways. First, we write standard job descriptions but also a technical piece that dictates the skills our company needs a candidate to display to gain the role.

Secondly, we have a promotion panel that gathers each week to talk about employeesā€™ internal growth. This takes away the yearly promotional cycle and replaces it with a promotion based on performance or on an as-needed basis.


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Federico Fregosi

Principal Consultant - AI & ML Practice at OpsGuru


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