![Bristlecone](https://media.trabajo.org/img/noimg.jpg)
Senior Engineer
3 weeks ago
ABOUT US :
Bristlecone is the leading provider of AI-powered application transformation services for the connected supply chain. We empower our customers with speed, visibility, automation, and resiliency – to thrive on change.
Our transformative solutions in Digital Logistics, Cognitive Manufacturing, Autonomous Planning, Smart Procurement and Digitalization are positioned around key industry pillars and delivered through a comprehensive portfolio of services spanning digital strategy, design and build, and implementation across a range of technology platforms.
Bristlecone is ranked among the top ten leaders in supply chain services by Gartner. We are headquartered in San Jose, California, with locations across North America, Europe and Asia, and over 2,500 consultants. Bristlecone is part of the $19.4 billion Mahindra Group.
We are seeking an experienced Senior Data Engineer to join our team on a long-term contracting basis. As a Senior Data Engineer, you will play a crucial role in designing, implementing, and maintaining scalable data pipelines using industry-leading tools such as Airflow, PySpark, and Databricks. You will also be responsible for supporting machine learning models in production, developing data products from large datasets, and collaborating with cross-functional teams to understand data needs and requirements.
Key Responsibilities:
- Design and implement scalable data pipelines using Airflow, PySpark, and Databricks.
- Support machine learning models in production to ensure their reliability and performance.
- Develop data products from large datasets to meet business needs and objectives for enterprise products.
- Collaborate with cross-functional teams to understand data needs and requirements, and translate them into technical solutions.
- Implement process monitoring to ensure reliability and data quality, including support for ACID transactions.
- Provide technical guidance and support to other team members as needed.
Requirements:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- At least 5 years of professional experience in a data engineering role, with a proven track record of delivering scalable and reliable data solutions.
- Extensive experience with Databricks, AWS, and Airflow ETL architectures, including supporting data streams from real-time consumer applications.
- Strong proficiency in Python, PySpark, and Spark SQL for data processing and analysis.
- Solid knowledge of SQL databases and data modeling principles.
- Familiarity with Databricks Lakeview and other data visualization tools for monitoring and reporting.
- Ability to work independently and in a team environment, with excellent problem-solving and communication skills.
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