Data Architect (DataBricks)

As a Data Architect at Envision Employment Solutions, you'll find yourself immersed in several exciting responsibilities. You'll design and implement data architectures using the Databricks platform, work on building data lakes and warehouses, and define data governance policies. Collaborating with data engineers is key, as you'll optimize data ingestion and processing pipelines. Additionally, you'll be responsible for maintaining data models for various business domains and ensuring data accuracy through profiling and quality assessments.

To qualify for the Data Architect position at Envision Employment Solutions, candidates should hold a Bachelor's degree in Computer Science or a related discipline and possess over 9 years of relevant experience. Strong expertise in Databricks, including Delta Lake and Spark SQL, is essential, along with familiarity with cloud services such as AWS, Azure, or GCP. Proficiency in SQL and Python, as well as knowledge of data integration, governance, and security practices, are also important for success in this role.

A successful Data Architect at Envision Employment Solutions should be proficient in several technical skills. Key among them are strong capabilities with Databricks technologies, including Delta Lake and Spark SQL, alongside cloud platform experience (AWS, Azure, GCP). Understanding data warehousing concepts, data modeling, ETL/ELT processes, and programming in SQL and Python will help you excel in this role. Additionally, experience in data governance and security best practices is a must.

Envision Employment Solutions values the growth and development of its employees, including Data Architects. The company supports career advancement through opportunities for learning and development. You can expect access to training, workshops, and mentorship programs, ensuring you stay current with industry trends and best practices. Additionally, employees are encouraged to take on new challenges and responsibilities to foster their career progression.

The Data Architect position at Envision Employment Solutions does offer flexibility regarding work hours, specifically aligning with US time zones. While remote work may be an option, candidates should be prepared for occasional travel abroad as necessary. This flexibility allows you to maintain a work-life balance while contributing effectively to the company's exciting data projects.

When answering this question, share specific projects where you utilized Databricks, emphasizing your role in designing data architectures or optimizing data pipelines. Detail the tools within Databricks that you've used, such as Delta Lake, and how you improved data processing efficiency.

To address this question effectively, describe your methodology for establishing data governance policies and implementing security measures in your data architectures. Provide examples of how you've ensured data integrity and compliance with industry standards.

Respond by highlighting your approach to data modeling, including the techniques you employ to design efficient schemas. Discuss your familiarity with different modeling approaches, such as star schema or snowflake schema, and how you've applied them in past projects.

Provide a detailed example of a data pipeline you've built, focusing on the technologies you used, the data sources involved, and the outcomes achieved. Highlight your role in the design and implementation phases and any challenges you overcame.

Discuss your strategies for data profiling and quality assessments, outlining the tools and techniques you use to monitor and enhance data accuracy. Provide examples of how you've identified and resolved data quality issues in past projects.

Share your experience working with cloud platforms, detailing the specific services you have utilized and how they integrate with data architectures. Highlight your understanding of cloud storage, database services, and data processing.

When answering, mention the resources you use to stay informed, such as online courses, industry blogs, and conferences. Emphasize your commitment to continuous learning and how it enhances your capabilities as a Data Architect.

Discuss your mentoring experiences, focusing on your teaching style and how you support junior team members' development. Provide specific examples of how you've helped them grow their skills or tackle complex challenges.

Explain your approach to simplifying complex technical concepts for non-technical audiences. Highlight examples of successful communication in previous roles and the tools you use to facilitate understanding, such as visual aids.

Clarify the differences between ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform). Discuss your experience with both processes, including when you would recommend one over the other based on the project requirements.