Consultant - R01544537

As a Consultant at Brillio, your primary responsibilities will include designing and implementing scalable data solutions using Snowflake, optimizing database performance, and leading data migration projects. You will collaborate with cross-functional teams to define requirements and deliver impactful data solutions while ensuring compliance and security best practices are followed.

To qualify for the Consultant role at Brillio, you should have a Bachelor's or Master’s degree in Computer Science or a related field, along with proven experience as a Snowflake Architect. Strong SQL skills, knowledge of data modeling techniques, and experience with cloud platforms are also essential. Familiarity with IICS tools and Pharma domain knowledge is particularly advantageous.

Yes, experience working with IQVIA data share is a must-have for the Consultant position at Brillio. Having this experience ensures that you can effectively contribute to projects that necessitate a deep understanding of the Pharma domain and relevant data handling.

The work environment for a Consultant at Brillio is dynamic and collaborative. You will work alongside passionate professionals in a culture that values innovation, client satisfaction, and personal development. Emphasis is placed on teamwork and leveraging the latest technology to achieve outstanding results.

Brillio is dedicated to fostering the professional growth of its Consultants. With a culture enriched by continuous learning opportunities, mentorship, and exposure to cutting-edge projects, you will find ample support to develop your technical and leadership skills throughout your career.

When designing data solutions using Snowflake, I start by understanding the business requirements and data workflows. From there, I focus on creating efficient data models to ensure optimal performance, implementing best practices for partitioning, indexing, and utilizing SnowPipe for data ingestion.

In my previous roles, I have successfully optimized SQL queries, adjusted warehouse sizes based on workloads, and utilized clustering keys to improve query response times. I believe that continuous monitoring and analysis are key to effective performance tuning in Snowflake.

Some key features I utilize include the separation of storage and compute, Snowflake's Time Travel for data recovery, and Zero-Copy Cloning for testing. These features significantly enhance flexibility and efficiency in data management.

I ensure data governance in Snowflake by implementing user access controls, encrypting sensitive data, and regularly reviewing compliance with security standards. Additionally, I work closely with governance teams to maintain data integrity policies across platforms.

I led a significant project that involved migrating legacy data systems to Snowflake. The challenge was to ensure minimal downtime while transforming and validating existing data. Through meticulous planning and execution, including iterative testing, we achieved a smooth transition.

My troubleshooting approach involves systematic investigation: starting with query logs, analyzing Snowflake’s performance statistics, and utilizing tools for monitoring and alerting. I also prioritize communication with team members to quickly identify and address issues collaboratively.

I often use tools like Informatica Cloud Services (IICS) for ETL processes, Apache Airflow for workflow management, and Python scripts for data manipulation. These tools complement Snowflake's capabilities to create robust data pipelines.

I regularly participate in webinars, read Snowflake community blogs, and follow industry updates. Engaging in hands-on practice with new features as they roll out helps me apply them to enhance our existing solutions effectively.

Data modeling plays a crucial role in my work as it lays the groundwork for data architecture. By aligning data models with business needs, I ensure that our data structures optimize performance and facilitate better analytics outcomes.

Collaboration is vital in data projects because diverse perspectives lead to more innovative solutions. Working closely with business analysts and stakeholders ensures that the data solutions developed truly meet the organization’s needs and drive value.