Databricks Engineer Risk Resources
Risk Resources
Office Location
Full Time
Experience: 3 - 3 years required
Pay:
Salary Information not included
Type: Full Time
Location: Maharashtra
Skills: Data Engineering, Data Modeling, data warehousing, data governance, data security, Databricks on AWS, pyspark, AWS Services, Data Processing Workflows, Data Pipeline Management
About Risk Resources
Job Description
You are an experienced Databricks on AWS and PySpark Engineer looking to join our team. Your role will involve designing, building, and maintaining large-scale data pipelines and architectures using Databricks on AWS and PySpark. You will also be responsible for developing and optimizing data processing workflows, collaborating with data scientists and analysts, ensuring data quality, security, and compliance, troubleshooting data pipeline issues, and staying updated with industry trends in data engineering and big data. Your responsibilities will include: - Designing, building, and maintaining large-scale data pipelines and architectures using Databricks on AWS and PySpark - Developing and optimizing data processing workflows using PySpark and Databricks - Collaborating with data scientists and analysts to design and implement data models and architectures - Ensuring data quality, security, and compliance with industry standards and regulations - Troubleshooting and resolving data pipeline issues and optimizing performance - Staying up-to-date with industry trends and emerging technologies in data engineering and big data Requirements: - 3+ years of experience in data engineering, with a focus on Databricks on AWS and PySpark - Strong expertise in PySpark and Databricks, including data processing, data modeling, and data warehousing - Experience with AWS services such as S3, Glue, and IAM - Strong understanding of data engineering principles, including data pipelines, data governance, and data security - Experience with data processing workflows and data pipeline management Soft Skills: - Excellent problem-solving skills and attention to detail - Strong communication and collaboration skills - Ability to work in a fast-paced, dynamic environment - Ability to adapt to changing requirements and priorities If you are a proactive and skilled professional with a passion for data engineering and a strong background in Databricks on AWS and PySpark, we encourage you to apply for this opportunity.,