Analytics Career Development at Meta
How we grow careers for top Data Science and Data Engineering pros
Analytics is a broad function at Meta. We have two primary job families: Data Science and Data Engineering, each comprising a wide variety of functional expertise. Working together, we aim to drive better outcomes, using data as a voice for our communities, and each job family brings unique strengths to the table. We run the gamut from building scalable infrastructure for exabytes of data, to delivering strategic insights based on rigorous analysis.
In this article, we’ll explore our overall approach to career development as an analytics org. Then, in future posts, we’ll dive into specific experiences and topics related to growth within the individual data science and data engineering functions.
Finding the right path for your skills and interests
In Analytics at our company — whether right out of school or coming from another field — typically learn and practice a common set of skills first. Once comfortable with the basics, they’ll take on more complex work. That could mean taking on more responsibility in a new or ambiguous product or technical area, or building deeper expertise within a domain. It could also mean making a move into people leadership. At Meta, we offer three types of career paths:
- Senior individual contributors do hands-on analysis or coding, lead by example with high-quality work, influence strategy or technical architecture, and mentor other analysts. They don’t directly manage people, but they help set direction in the team and influence decisions at every level.
- Org builder managers focus on the strategy and priorities of a larger team, coach and develop career paths with their team members, and ensure the quality of output is high. It’s also not uncommon to find org builder managers doing hands-on analysis or coding.
- Tech lead managers split their time between individual contributions and managing a small team. This career path is less common than focusing entirely on individual work or management. But, it can be a great fit for individuals who want to develop deep experience in a technical problem or domain. They get to stay hands-on while also leading people.
In some companies, career progression implies transitioning into management. At Meta, becoming a manager is not a “promotion”. It’s just another way to get work done. People can (and quite often do) move between managing and individual contribution over their careers, depending on what makes the most sense for them at the time. Notably, at Meta, this is not at all detrimental to a person’s promotion path. It is possible to grow to Director level and beyond as an Org Leader, Tech Lead Manager, or Individual Contributor. These paths provide maximum flexibility in how people choose to grow their careers. They allow people to focus on their true strengths without worrying about promotion limitations.
Focus on your strengths, not one-size-fits-all
Analytics can mean a lot of different things. While we expect a well-rounded base, there isn’t a one-size-fits-all set of skills or tasks that everyone does equally well within the company. Senior individual contributors tend to specialize more as their careers develop to the most senior levels. Those differences are something we embrace and amplify.
We use a set of “archetypes” to describe some of those common variations on strengths and focus areas. For example:
- Technical and coding expertise, including designing complex systems for efficiency or pioneering new analysis techniques when they’re needed
- Product or business expertise, creatively applying data to the most critical strategic questions, and making sense of new areas
- Domain expertise in a particular subject, like applied machine learning, auction systems, fraud-prevention systems, or search analytics, to name a few examples.
- General know-how, able to do whatever is needed in various new or challenging areas, often getting the team pointed in the right direction before moving on to the next challenge.
It’s an adventure, not a ladder
There isn’t just one way to grow a successful career in Analytics at Meta. There aren’t predetermined paths with checklists of work laid out. Of course, that’s part of the fun and opportunity of working in analytics — but it also takes creativity and an open mind to plan a career.
The products and teams at Meta grow and change quickly. As a result, our analytical capabilities need to adapt even more rapidly. We strive day-in-day-out to use data efficiently, effectively, and with privacy baked into everything we do.
People working in Analytics will often try out a range of projects and teams or even move jobs between data science, data engineering, and other types of functions. Others stick in one area and develop deep expertise. The key is for each person to develop a sense of what’s most exciting and fulfilling for them, get a sense of what they’re best at (or can be best at), and find the intersection of those interests and skills.
Building your support system and paying it forward
People’s careers are ultimately in their own hands at Meta, but we support career development via a comprehensive support network:
- Managers work with people on their teams day-to-day, plan career development, give feedback, and help unblock people when they’re stuck, among other things. Managers will help establish long-term career goals, line up strengths-aligned work, and help find new challenges to develop desired experience.
- Mentors are trusted peers who provide advice and guidance. A manager can also be a mentor, but more often, mentors will be senior-level colleagues. The company has a system to match mentors and mentees based on career development goals and priorities. It’s valuable to get perspective and advice from people who have worked in different areas, roles, or companies in their own careers.
- Circles match up groups of people with similar interests or career paths. They get together regularly to share experiences and learn from each other. Like mentorship, the shared support and advice beyond direct managers can be invaluable to learning new skills, making new connections, and spotting common patterns across analytics problems.
- Learning & Development courses tackle a range of skills, from technical design and architecture to effective communication, management approaches, and advanced analytics methodologies. There’s a dedicated team that helps develop and run this content for Analytics. Most of the courses are taught by Data Scientists and Data Engineers, and it’s a great way to “pay it forward” for other people who are earlier in their careers or newer to a skill.
Check out Analytics Careers at Meta
You can browse and apply for open roles at facebook.com/careers, or share with friends and colleagues who might be interested. We’re hiring full-time Remote positions that let you work from anywhere in the US or Canada, in addition to roles in our offices around the world.
Authors: Steve D., Nick W., and Justin G.
