Lead Data Engineer - Managed Services

As a Lead Data Engineer - Managed Services at Hakkōda, you will be responsible for monitoring and improving software system reliability, collaborating with customers and internal teams to address their needs, and building effective monitoring systems. Additionally, you will mentor and coach associates, oversee the engineering support for large-scale applications, and contribute to designing data warehouses and developing ETL/ELT ingestion pipelines.

To apply for the Lead Data Engineer - Managed Services position at Hakkōda, you should have a Bachelor's degree in Data Analytics, Computer Science, or a related field, with at least four years of relevant technical experience and a minimum of one year in a leadership role. Familiarity with SQL, data warehousing, cloud technologies, and tools like DataStage or Informatica is also important for this role.

Hakkōda is committed to the growth of its Lead Data Engineers by providing access to technical training and certification programs. This encourages your continuous learning in the dynamic field of data engineering, allowing you to stay current on the latest technologies and methodologies that can benefit both you and our clients.

At Hakkōda, the work environment for a Lead Data Engineer is flexible and supportive. You can choose to work remotely or utilize our cozy co-working space in Lisbon. We foster a culture of open communication and collaboration, making it a positive and fun team dynamic, where associates feel encouraged to share ideas and challenge themselves.

In your role as a Lead Data Engineer - Managed Services at Hakkōda, you will be involved in various projects that focus on improving system performance, managing large-scale software applications, and designing innovative data solutions. You will also play a crucial role in identifying performance bottlenecks and designing efficient ETL/ELT pipelines, ensuring our client's data needs are met proactively.

When answering this question, provide specific examples of data warehousing technologies you've worked with, such as Teradata or Oracle Exadata. Discuss the projects you contributed to, your role in designing or optimizing these systems, and how your contributions helped enhance the overall data management strategy.

Discuss your proactive approach to system monitoring, the use of performance metrics, and the methodologies you've employed to identify and resolve bottlenecks. Give examples of tools you've used for system monitoring and how you've implemented processes for continual improvement.

Outline the essential stages of an ETL/ELT pipeline, such as extraction, transformation, and loading, and elaborate on the tools you’ve used to build these pipelines. Provide examples of how you’ve optimized these components for performance and efficiency in past projects.

Share your leadership philosophy and specific strategies for managing a technical team, such as setting clear goals, providing mentorship, encouraging open communication, and fostering a collaborative environment. Include examples of challenges you've faced and how you overcame them.

Mention specific cloud platforms you’ve worked with, such as AWS or Snowflake. Discuss how you've utilized these technologies to improve data management, storage solutions, or analytical capabilities, and provide insights into the advantages they offered in your projects.

Choose a challenging data-related issue you encountered, explain its context, your thought process in analyzing the problem, and the steps you took to resolve it. Highlight the impact of your solution on the business or project outcomes.

Explain your experience with various data visualization tools, such as Tableau or Power BI, and discuss how you've used them to communicate insights effectively. Mention any processes you follow to ensure that visualizations are clear, informative, and tailored to the audience.

Discuss the methodologies you implement for continuous improvement, such as Agile practices, regular code reviews, and utilizing feedback from peers. Provide examples of how these practices have led to successful project outcomes and personal growth.

Emphasize the importance of gathering and incorporating customer feedback into your projects. Discuss how you engage with clients throughout development phases to understand their needs and make necessary adjustments to ensure satisfaction and project success.

Mention the resources and strategies you use to stay informed about the latest trends in data engineering, such as webinars, online courses, and industry publications. Share how you’ve applied new knowledge to enhance your work and improve your team’s performance.