Data Solutions Architect

2 weeks ago

India beBeeData Full time ₹ 1,50,00,000 - ₹ 2,00,00,000
Join Our Data Engineering Team

We're looking for a skilled data engineer to lead the way in software development and drive transformative solutions that harness the power of data.

  • Key Responsibilities:
  • Design and implement scalable ETL/data pipelines using Python and Luigi for efficient data processing.
  • Guarantee high-volume clickstream, demographics, and business data processing efficiency.
  • Advise the team on best practices for data pipeline development, code quality, and performance optimization.
  • Configure, deploy, and maintain AWS infrastructure to ensure scalability, availability, and security.
  • Support data storage and retrieval workflows using S3 and SQL-based storage solutions.
  • Provide architectural guidance for cloud-native data solutions and infrastructure design.
  • Oversee legacy framework maintenance and propose comprehensive cloud migration or modernization plans.
  • Lead large-scale data migration initiatives to Snowflake, ensuring data integrity, security, and minimal business disruption.
  • Coordinate infrastructure changes with stakeholders to align with business needs.
  • Develop robust monitoring solutions to track system health, performance, and data pipeline accuracy.
  • Set up alerts and dashboards for proactive issue detection and collaborate with cross-functional teams to resolve critical issues.

As a key member of our team, you will work closely with dynamic professionals to drive innovation, adopt cutting-edge technologies, and develop expertise in data engineering solutions.

Requirements:
  • A minimum of 6 years of experience in data engineering or a related technical field.
  • At least 4 years of experience in Snowflake projects.
  • Proven expertise with Snowflake data warehousing, including schema design, efficient data loading, and performance tuning.
  • Strong programming skills in Python for automation and data workflows.
  • Expertise in managing SQL databases for data storage and query optimization.
  • Familiarity with monitoring solutions for real-time tracking and troubleshooting of data pipelines.

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