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Knowledge and skills for successful data leadership
17 hours ago
In this story, I would like to talk about the essential skills and knowledge I would want to equip myself fifteen years ago to succeed in the data engineering space. Leadership role in engineering requires more technical focus and hands-on activities to guide the dev team towards that optimal and desired outcome set as a project goal. There is a lot to discuss in architecture and technical standards, communicating effectively with major stakeholders, and ensuring that projects are delivered to a high degree of technical quality. Ideally, I would like to rewind fifteen years of my career back and see what I need to become a successful data engineering lead. Throughout my almost fifteen-year career in analytics and tech, I have seen many things. This story is a summary of lessons I have learned.
It is true that there aren’t many leadership resources available for Lead Data Engineers, and most tech leadership references are for Data Analytics Managers overseeing the team of analysts to ensure that projects are delivered on time and within the budget.
Data engineering is an exciting and very rewarding field. The companies will always hire someone who knows how to process (ETL) data efficiently.
It definitely won’t be boring and it pays well.
In one of my previous stories, I wrote about the role without the “Lead” prefix, what’s included, what to expect and how to comply with requirements [1]. However, the “Lead” prefix requires more focus on leadership and soft skills development.
The role pays well because not an easy task to build a good and efficient data platform that provides value. It requires considerable technical expertise and solid coding skills. Consider data engineering as a combination of analytics and software engineering. The role would require certain abilities to merge these skill sets to build a robust data…
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