How can data engineers help their team members learn new skills?

O compartilhamento de conhecimento é uma excelente forma de engajar o time com rela??o aos propósitos e metas. Liderar pelo exemplo é inspirador e contribui para um ambiente produtivo e focado na entrega de resultados. O gestor deve promover a colabora??o interfuncional do time estabelecendo metas e objetivos compartilhados sempre orientados ao resultado final e entrega de valor para área de negócio. A forma??o de times ágeis e multidisciplinares que atuam baseados nas metodologias ágeis, como Scrum, Kanban, SAFe, XP entre outras ajudam no dia a dia dos projetos garantindo a colabora??o entre os membros do time e a melhoria contínua sempre com foco no cliente. Celebre sempre as conquistas do seu time!

I am a big advocate for knowledge sharing - especially in the technical space. Just having the knack to share knowledge based on an idea can lead to making something better or optimising a certain process within a system. This is why working with like-minded senior engineers is great. You can share knowledge, they can understand you and make you better in 'bouncing ideas' off each other. Knowledge sharing can also come in the form of asking curious questions when stuck with a certain problem. Asking can and most often allows others to share with you. Enables you to learn a certain technique a different way or learn a new topic altogether. Knowledge sharing will always remain key to upskilling and working up the ladder.

Data engineers can help their team members learn new skills by mentoring, organizing training workshops, sharing resources, engaging in pair programming, encouraging collaboration, and setting learning goals. These strategies can foster a culture of continuous learning and contribute to the team's overall success.

Team members can help each other through knowledge-sharing sessions. Whether you have developed a new component within your organizational system or learned a new technology, it is always good to document the whole process because it helps your peers as well as new team members in the future as well. It holds whether you're a data engineer or not. Furthermore, it helps you as well as you get better when you share the knowledge and get better by discovering more scenarios.

O feedback definitivamente é uma excelente ferramenta para o aprendizado e aprimoramento da performance no trabalho. Além de demonstrar respeito ao profissional ajuda no direcionamento do mesmo rumo as metas e objetivos individuais e organizacionais.

?? A great way to teach others new skills is apply live tutorial with them to help from technical and theorical view learn all aspect of the new skill. ??When i apply this methods for data members, all members resolve common question in one time, feel more secure about their learning and learn more by generated questions from group.

Data Engineering is tough. And it is very hard to learn everything by yourself. The best way that worked for me to learn new tools is pair programming. Try to provide as much feedback as possible. And if you are stuck at something, it is always preferred to ask for different perspective. Since the field is very vast and complicated, there is always going to be something you understand better than your peers. In that case do not hesitate to organize knowledge sharing sessions. Remember that we all are in the same boat, and communication is the key for achieving goals and targets.

In my professional experience, I learn a lot by practicing, testing and experimenting with different resolutions to the problem and talking to other team members. The flexibility to try different solutions is a great advantage for evaluating solution efficiency. Working in pair code also helps a lot to know different solutions to the same problem.

???? In my experiences; apply your technical skills in test environment or PoC to solve any problem in your work, as well create a project in your portfolio to show your new skill: the point is show your experimentation, applied criterias and knowledge and document it for other learn based its.

Collaboration with other teams is very important to understand data and acquire insights about it. In my experience, having cross-team projects helps us to gain more detailed domain knowledge. Sometimes we might not know where the data is coming from, and what it represents. But if you collaborate constantly, there will be fewer chances of misunderstanding and incorrect insights. During collaboration, keep in mind to document learned knowledge as much as possible, despite it being very tedious. in the long run you and your peers will thank you for that.

Essa é mais uma das principais motiva??es em quebrar tarefas muito grandes em escopo menores. O time consegue reconhecer o próprio avan?o com entregas que gerem valor para a companhia semana após semana. A ideia é, entregas pequenas de forma constante que impacte o negócio. Estamos acostumados a respirar fundo para dar um grande mergulho, quando na verdade, manter o ritmo de respirar, celebrar, atacar novamente é a chave para manter um time engajado e com propósito. Todo avan?o fica mais claro, n?o apenas nas entregas, mas na maturidade do time tecnicamente. Por consequência, o aprendizado vem, de forma constante também.