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A Day in the Life of the SVP of Data at The Muse

Catherine Pargeter, the SVP of Data at The Muse
Catherine Pargeter, the SVP of Data at The Muse.
| Courtesy of The Muse

Name: Catherine Pargeter
Title: SVP of Data at The Muse
Hobbies: Running, bread making, knitting, sewing, chasing small children, folding endless piles of laundry while watching Star Wars
Location: New York

Catherine joined The Muse in 2021 as the Director of Data. During her tenure, she has earned two promotions and currently leads a team of data engineers and analysts. “My team is amazing, and I love working through issues with them,” she says. “Sometimes, I get to show little tricks of our technologies, like the coding validation our business intelligence tool provides to help spot issues before we roll out code changes.”

Check out how she spends a typical day working from her home in Manhattan.

6:30 a.m.

I wake up but pretend to be asleep until my kids came in at 7:02 a.m. on the dot. I have a 6-year-old and an almost 4-year-old, and the youngest bounces out of bed as soon as the sun comes up. I get my oldest to school by 8:15, and then get home to clean up from breakfast. Working from home means that if I need to run a load of laundry midday, I can—but it also means that if the house is a huge mess, I am working in a mess unless I clean it up.

9 a.m.

I sit down at my desk, checking Slack first, then emails. We had a few data questions come in from account managers first thing, and I usually prioritize those to make sure our clients’ questions get answered quickly. I also do a data pull for the upcoming board meeting and get back to one of our engineers waiting on a spec.

10:30 a.m.

I’m actively hiring for a senior data engineer role on my team, so I have a lot of initial screening calls. I love hearing everyone’s backgrounds, how they think about data engineering, and how it fits into the larger data ecosystem. I always ask a question about a specific project they are most proud of, and I love it when someone geeks out on describing super complex work that they did that brings them joy.

11 a.m.

Three times a week, the data team meets for 15 minutes to have our standup. Everyone talks about what they did the day before, what they are doing today, and any blockers that they have. Blockers can be anything from “I’m waiting for this person to do X so I can do Y,” “we have a bug and I can’t move forward until the bug is fixed,” or “I don’t know how to proceed with my work.” I help unblock the team when I can or ask for help from engineering or other teams to get them what they need.

12 p.m.

My calendar is blocked for an hour every day for lunch. On days when I haven’t gone for a run in the morning, I use it as my run time.

1 p.m.

We are progressing through the update of our data warehouse, so there have been a lot of architectural and procedural decisions that we have had to make. Therefore, we organized a weekly meeting of our data engineers to focus on these decisions and make sure that we are all aligned as we progress.

2 p.m. to 3:30 p.m.

I have meetings with our product team manager and then the content team. Data supports teams across the organization, all of which have very different needs. It’s challenging but means that we always have interesting projects in the backlog. Right now, we are looking to implement eventing on some new product features.

3:30 p.m.

I start to get dinner together in between meetings. My whole family has a cold, so I’m making a broth that needs a good hour to simmer before I use it in soup. This is such a huge benefit of working from home—being able to plop veggies into a pot and let them simmer while discussing analytics.

4:30 p.m.

I leave to pick up my daughters for swim class. It’s a time to both watch them swim, but also to catch up on any Slack messages that I didn’t have a chance to review during the day.

8 p.m.

My husband and I have a rule where we don’t work one night per week, which we started in 2020. He is in academia, so there are always more grants or papers to write, assignments to grade, and classes to prep for. If we don’t watch it, we would both work ourselves straight into burnout. Instead, tonight we watch The Marvelous Mrs. Maisel.