Data Lead

As a Data Lead at ShyftLabs, your primary responsibilities include leading the development and implementation of data features for our booking and content management systems, managing robust data pipelines, and overseeing the data infrastructure across multiple environments. You will collaborate with Data PMs, support client data queries, and manage a team of engineers and analysts to ensure the delivery of high-quality data solutions.

To qualify for the Data Lead role at ShyftLabs, candidates should have at least 8 years of experience in data engineering or analytics, with a strong focus on infrastructure and data modeling. Additionally, leadership experience managing a data team and proficiency in SQL, Python, and modern data stack tools like DBT and Databricks are crucial to succeed in this position.

A Data Lead at ShyftLabs should be proficient in SQL and Python, with experience using data pipeline tools like Airflow, DBT, and Databricks. Understanding distributed NoSQL databases such as Cassandra and MongoDB, along with cloud data warehouses like Snowflake or BigQuery, is also essential for managing and optimizing the data systems effectively.

ShyftLabs is committed to the growth of its employees and provides extensive learning and development resources. As a Data Lead, you will have access to various opportunities for professional development including mentorship, training programs, and the ability to work on complex data features that enhance your skills and career.

The working environment at ShyftLabs is dynamic and collaborative, with a hybrid model allowing for two days per week in the office. We promote a culture of inclusivity and diversity, where your contributions are valued, and you are encouraged to innovate and push boundaries in your role as a Data Lead.

When answering this question, emphasize your hands-on experience designing and implementing data pipelines. Discuss specific tools you've used like Airflow and Databricks, and provide examples of how you ensured data accuracy and efficiency in your pipeline architecture.

In your response, highlight your leadership style, methods for mentoring team members, and how you ensure team productivity. Provide examples of how you’ve fostered a collaborative environment and encouraged professional growth.

Discuss specific strategies you implement for data quality control, such as data validation processes, implementing monitoring tools, and encouraging best practices in your team for data governance and documentation to maintain high standards of data quality.

Use this opportunity to walk the interviewer through a specific data challenge, detailing the problem, your thought process, the solution you implemented, and the outcome. This demonstrates not only your technical skills but problem-solving ability as well.

Talk about the frameworks you use for prioritization, such as agile methodologies. Mention how you gather insights from stakeholders, align with business goals, and balance immediate client needs with long-term project planning.

Be prepared to discuss the various technology stacks you’ve worked with, such as specific NoSQL databases, cloud platforms, and data processing tools. Explain your experience level with each and how they contributed to successful data projects.

Discuss approaches you’ve taken for optimizing performance in distributed systems. Mention specific techniques, tools, or previous experiences that demonstrate your ability to enhance system performance and manage resources efficiently.

Emphasize how you establish clear communication channels with stakeholders, the importance of regular updates, and how you tailor your messaging based on your audience's technical understanding to keep them informed and engaged throughout data projects.

Provide examples of how you have implemented data governance policies and ensured compliance with regulations like GDPR. Discuss your understanding of the importance of data ethics and how they influence your data management practices.

When answering, connect your personal career aspirations with ShyftLabs' values and mission. Explain how you align with the company’s goals of innovation and scaling data solutions, and why you are excited about the opportunity to make an impactful contribution.