Pros: - Great work culture; it will always keep you on your toes when it comes to Data & AI consultation. - Helpful people; no one underestimates anyone, and everyone is treated equally. - Field Engineering & Professional Services is really strong and knows how to solve their customers' problems. - Good communication channels exist between FE teams, customers, and product. - Good salary and good perks, basically whatever it takes to keep an employee motivated and happy. - Good work/life balance. As an Individual Contributor, you're basically your own boss and you bill the customer directly. Project Managers & Engagement Managers are also helpful in managing workloads.

Cons: Some products are too much of an overkill, like DLT or DAB. Sometimes, it seems there is less intervention from field engineering on products as to what has to be delivered, or it is an ask from a customer. Regional politics, a common scenario, still happens at Databricks. Central EMEA folks will not like the solutions of Northern EMEA, and vice versa. Sometimes this puts us in jeopardy, and it's really hard to tell who is what. Sometimes, there are monotonous engagements that feel like you're not going anywhere with your career. For example, you could be doing CI/CD for customers and be stuck with it.

Pros: Strong mentorship and many opportunities to learn new data tools and ML workflows. Collaborative team atmosphere with regular knowledge-sharing sessions. Competitive salary and comprehensive benefits package. Flexible work-from-home policy and supportive manager.

Cons: Rapid product changes sometimes cause shifting priorities and workload spikes. Onboarding documentation could be more complete for new hires.

Pros: - Fun, energetic, and positive work environment. - Flexible work/life balance (in the field, at least). - Good remuneration. - Lots of technically challenging work. - Leadership is transparent and open to feedback.

Cons: Constant product changes can be exhausting to keep up with and try to sell. A very engineering-led company can cause issues sometimes. Engineering can tend to look down on the field, and as a result either don't listen to or are just dismissive of product feedback.