Data Lead | Las Vegas | Credit One Bank

As a Data Lead at Credit One Bank, your responsibilities encompass driving data strategy and governance, overseeing data architecture, and leading data engineering efforts. You will ensure the implementation of data governance policies, design scalable data architectures, and collaborate with teams to support analytics initiatives.

To qualify for the Data Lead position at Credit One Bank, candidates should have a Bachelor’s or Master’s degree in fields like Computer Science or Data Science and extensive experience in data management or engineering. Proficiency in SQL and big data technologies such as Spark or Hadoop is also essential.

The salary range for the Data Lead position at Credit One Bank is between USD 34,000 and USD 120,000, depending on the candidate's experience and qualifications. This broad range reflects our commitment to fair compensation based on individual capabilities.

A successful Data Lead at Credit One Bank should be familiar with various technologies including SQL, NoSQL databases, cloud platforms like AWS or Azure, and big data technologies such as Hadoop and Spark. Knowledge in ETL/ELT processes and data warehousing solutions like Snowflake is also vital.

As a Data Lead at Credit One Bank, you can expect a comprehensive benefits package that includes medical, vision, and dental coverage, a 401k retirement plan, paid time off, and paid holidays. We prioritize the wellbeing of our employees.

In your response, emphasize your familiarity with defining and implementing data governance policies. Discuss specific frameworks you've used and how you ensured compliance with regulations like GDPR or HIPAA in your previous roles.

When answering this question, outline your methodology for understanding business requirements and translating them into scalable data architectures. Provide examples of data lakes or warehouses you've designed and the impact on analytics.

Share your experience optimizing ETL/ELT processes, detailing specific tools and techniques used. Highlight instances where you improved data ingestion and transformation speeds, and how those improvements benefitted the organization.

Discuss the big data technologies you're familiar with, such as Hadoop or Spark. Provide examples of projects where you've implemented these technologies and the results of your contributions.

Explain your mentoring style, focusing on how you encourage skill development and foster a culture of innovation. Share examples where you've successfully guided team members through challenges.

Describe a situation where you managed a conflict, highlighting your communication and problem-solving strategies. Emphasize the importance of collaboration and how you ensured a positive resolution.

Discuss your familiarity with various data visualization tools like Tableau or Power BI. Provide insights on how these tools can help in presenting data effectively to stakeholders.

Mention your hands-on experience with cloud platforms like AWS, Azure, or GCP. Highlight specific services you've utilized, such as data warehousing or analytics services, and how they enhanced your projects.

Share your strategies for effective stakeholder management, detailing how you identify their needs and communicate insights. Provide times when your approach helped bridge gaps between technical and non-technical teams.

In your response, reflect on aspects of data leadership that excite you, such as driving innovation or enabling data-driven decision-making. Share personal stories that inspired your passion for data.