ABOUT BRISTLECONE
Bristlecone, the trusted partner in supply chain transformation, specializes in building antifragile supply chains that adapt to inevitable change and deliver positive customer experiences. We create certainty and unlock value. We are a part of Mahindra, a global federation of companies with 240,000 employees and presence in more than 100 countries. Please visit www.bristlecone.com for more information about Bristlecone.
Databricks Engineer
As a Databricks Engineer, you will play a pivotal role in designing, implementing, and optimizing data processing pipelines and analytics solutions on the Databricks platform. You will collaborate closely with cross-functional teams to understand business requirements, architect scalable solutions, and ensure the reliability and performance of our data infrastructure. This role requires deep expertise in Databricks, strong programming skills, and a passion for solving complex engineering challenges.
What you'll do:
- Design and develop data processing pipelines and analytics solutions using Databricks.
- Architect scalable and efficient data models and storage solutions on the Databricks platform.
- Collaborate with architects and other teams to migrate current solution to use Databricks.
- Optimize performance and reliability of Databricks clusters and jobs to meet SLAs and business requirements.
- Use best practices for data governance, security, and compliance on the Databricks platform.
- Mentor junior engineers and provide technical guidance.
- Stay current with emerging technologies and trends in data engineering and analytics to drive continuous improvement.
You'll be expected to have:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- 5 to 8 years of overall experience and 2+ years of experience designing and implementing data solutions on the Databricks platform.
- Proficiency in programming languages such as Python, Scala, or SQL.
- Strong understanding of distributed computing principles and experience with big data technologies such as Apache Spark.
- Experience with cloud platforms such as AWS, Azure, or GCP, and their associated data services.
- Proven track record of delivering scalable and reliable data solutions in a fast-paced environment.
- Excellent problem-solving skills and attention to detail.
- Strong communication and collaboration skills with the ability to work effectively in cross-functional teams.
- Good to have experience with containerization technologies such as Docker and Kubernetes.
- Knowledge of DevOps practices for automated deployment and monitoring of data pipelines.
