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Data Engineer

Leonardo.ai is an Australian technology start-up. Our AI-powered platform allows users to create production-quality visual assets with unprecedented quality, speed, and style. Join us as we embark on an exciting journey, building our next generation of products and features to achieve our mission. Unleash Creativity with the power of AI. 

The Role: 

We are looking for a Data Engineer / DataOps Engineer with Cloud experience. The goal is to provide a seamless flow of information throughout the company, considering both backend data structure and frontend accessibility for end-users.

Joining an existing team of three, you will be working across a variety of tasks, primarily cloud engineering,establishing best practice and building out our Data Lakehouse in AWS. Given the scale of the team, there will be times whereby you will advise and architect the data lifecycle at Leonardo. To a lesser extent, you will also be provisioning and maintaining the data clusters.

What you'll do:

  • Extend the existing data processes, primarily scaling the data lakehouse. 

  • Supporting, advising and upskilling the existing team around data best practice

  • Data Architecture, modelling and advice. 

  • Maintain a holistic view of Leonardo’s data lifecycle.

  • Build database systems of high availability and quality depending on each end user’s specialised role

  • Provide proactive and reactive data management support and training to users

  • Perform tests and evaluations regularly to ensure data security, privacy and integrity

Skills we like:

  • Hands-on experience with a datalake in AWS, S3, Glue, Redshift, Parquet, RDS

  • Hands-on experience with PostgreSQL, database standards and end-user applications

  • Familiarity with programming languages, JS, Python, Terraform among others.

What's in it for you?

A range of benefits to set you up for every success in and outside of work. Here's a taste of what's on offer:

  • Impact the future of AI

  • Reward package including equity - we want our success to be yours too

  • Inclusive parental leave policy that supports all parents & carers with 18 weeks paid leave

  • An annual Vibe & Thrive allowance to support your wellbeing, social connection, office setup & more

  • Flexible leave options that empower you to be a force for good, take time to recharge and supports you personally, including remote working abroad

  • Support with your professional development

  • Fun and engaging company events, both virtual and in-person

  • 20 days annual leave

  • Novated car leasing

We're committed to building a diverse, safe and inclusive environment where employees can be authentic, and teams collaborate effectively to bring innovative ideas to life.

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What You Should Know About Data Engineer, Leonardo.Ai

At Leonardo.ai, we're on a mission to revolutionize the way users create visual assets with the power of AI. As a Data Engineer in Sydney, you will play a crucial role in building our next generation of products that pushes the boundaries of creativity. You'll be joining a dynamic, friendly team of three, focusing on enhancing our data infrastructure and ensuring a smooth flow of information across the company. Your day-to-day will revolve around working with AWS to scale our data lakehouse, while also providing essential support and best practices to your teammates. You'll have the chance to showcase your expertise in data architecture and modeling, all while maintaining a strong oversight of Leonardo's data lifecycle. We believe that a well-structured data system is key to empowering our end-users, and your contributions will help build robust database systems tailored to their needs. In addition, you'll be involved in proactive data management, ensuring data security, privacy, and integrity through regular evaluations and tests. Prepare to immerse yourself in a vibrant culture that encourages professional development and recognizes your successes. Join us, and let’s create exceptional AI-powered experiences together, making an impactful difference in the industry!

Frequently Asked Questions (FAQs) for Data Engineer Role at Leonardo.Ai
What are the primary responsibilities of a Data Engineer at Leonardo.ai?

As a Data Engineer at Leonardo.ai, your primary responsibilities will include scaling the data lakehouse in AWS, extending existing data processes, and advising the team on best practices. You'll also be responsible for data architecture and modeling, maintaining a holistic view of the data lifecycle, and providing both proactive and reactive data management support to end-users.

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What qualifications do I need to apply for the Data Engineer position at Leonardo.ai?

To apply for the Data Engineer position at Leonardo.ai, you should have hands-on experience with AWS data lakes, including services like S3, Glue, Redshift, and RDS, as well as proficiency in PostgreSQL. Familiarity with programming languages such as JavaScript, Python, and Terraform is also advantageous. A strong understanding of data management practices and a commitment to data security and integrity are essential.

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How does Leonardo.ai support professional development for its Data Engineers?

Leonardo.ai is committed to the professional growth of its team members, including Data Engineers. We offer support for continuous learning, including training programs, workshops, and opportunities to attend industry events. We want you to not only grow in your role but thrive in your career!

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What tools will I be using as a Data Engineer at Leonardo.ai?

As a Data Engineer at Leonardo.ai, you will utilize various tools and technologies including AWS services like S3, Glue, Redshift, and Parquet, alongside PostgreSQL for database management. You'll also work with programming languages such as JavaScript, Python, and Terraform, contributing to the design and implementation of our data solutions.

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How flexible are the work arrangements for the Data Engineer role at Leonardo.ai?

At Leonardo.ai, we value work-life balance and offer flexible work arrangements for our Data Engineer role. This includes options for remote work, flexible leave policies, and opportunities to work abroad, allowing you to recharge and take care of your personal needs while contributing to our innovative projects.

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Common Interview Questions for Data Engineer
Can you explain your experience with AWS data lakes?

In an interview, emphasize specific projects where you worked with AWS data lakes, detailing services like S3 and Redshift that you utilized. Describe how you scaled data solutions and ensured data integrity, showcasing your technical skills and ability to collaborate within a team.

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How do you ensure data security and privacy in your projects?

Discuss your approach to data security by outlining frameworks or practices you've implemented to protect sensitive information. This could include encryption methods, access controls, and regular audits, demonstrating your commitment to safeguarding data integrity.

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What strategies do you use for data architecture and modeling?

Highlight your methodologies for data architecture, such as entity-relationship modeling or dimensional modeling. Provide examples of successful implementations and how you adjusted architecture based on user needs and data accessibility.

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Describe a challenging data problem you faced and how you solved it.

Provide a specific example of a complex data issue you encountered. Explain the steps you took to diagnose the problem, the tools you used, and the outcome of your solution, emphasizing your analytical and problem-solving skills.

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How do you keep up with the latest trends in data engineering?

Share your strategies for staying informed about industry trends, such as following thought leaders on social media, participating in webinars, and reading relevant articles or journals. This shows your commitment to continuous learning in the field.

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How do you approach collaboration with team members?

Discuss your communication style and techniques for effectively collaborating with colleagues on data projects. Mention tools you use for collaboration, such as Slack or Jira, and share examples of how teamwork contributed to project success.

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What experience do you have with data management best practices?

Explain your understanding of data management best practices, covering topics like data governance, quality assurance, and lifecycle management. Provide examples of how you’ve implemented these practices in past roles to enhance data usability.

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Can you describe a scenario where you upskilled a team member in data practices?

Share a specific instance where you mentored a colleague in data practices. Discuss the methods you used to convey information, the resources you provided, and the positive outcome of your mentorship for both the individual and the team.

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What programming languages are you comfortable with for data engineering tasks?

List programming languages you are proficient in, such as Python, JavaScript, or Terraform. Share examples of projects where you used these languages, highlighting your technical skills and how they contributed to project success.

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What would you consider while designing a high-availability data system?

Discuss factors such as load balancing, redundancy, failover mechanisms, and user needs that you take into account while designing high-availability systems. Providing real-world scenarios where you've applied these considerations will illustrate your expertise.

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Full-time, remote
DATE POSTED
December 13, 2024

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