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Join Ads Marketplace to earn through podcast sponsorships.
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Get the answers and support you need.
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Stay updated with the latest podcasting tips and trends.
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Podcast interviews, best practices, and helpful tips.
The step-by-step guide to start your own podcast.
Create the best live podcast and engage your audience.
Tips on making the decision to monetize your podcast.
The best ways to get more eyes and ears on your podcast.
Everything you need to know about podcast advertising.
The ultimate guide to recording a podcast on your phone.
Steps to set up and use group recording in the Podbean app.
#209 Effective Data Engineering with Liya Aizenberg, Director of Data Engineering at Away
Building a successful data engineering team involves more than just hiring skilled individuals—it requires fostering a culture of trust, collaboration, and continuous learning. But how do you start from scratch and create a team that not only meets technical demands but also drives business value? What key traits should you look for in your early hires, and how do you ensure your team’s projects align with the company’s goals?
Liya Aizenberg is Director of Data Engineering at Away and a seasoned data leader with over 22 years of experience spearheading innovation in scalable data engineering pipelines and distribution solutions. She has built successful data teams that integrate seamlessly with various business functions, serving as invaluable organizational partners. She focuses on promoting data-driven approaches to empower organizations to make proactive decisions based on timely and organized data, shifting from reactive to proactive business strategies. Additionally, as a passionate advocate for Women in Tech, she actively contributes to fostering diversity and inclusion in the technology industry.
In the episode, Adel and Liya explore the key attributes that forge an effective data engineering team, traits to look for in new hires, what technical skill sets set people up for success in a data engineering team, leveraging knowledge transfer between external experts and internal stakeholders, upskilling and career growth, aligning data engineering initiatives with business goals, measuring the ROI of data projects, working agile in data engineering, balancing innovation and practicality, future trends and much more.
Links Mentioned in the Show:
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