Description

You will lead the design, development, and deployment of scalable data engineering solutions for operational and analytical data delivery.

Responsibilities

• Design and implement data pipelines and workflows in collaboration with data scientists and analysts.
• Develop and maintain data warehousing solutions using Snowflake and manage ETL pipelines via AWS Glue, Spark, and Databricks.
• Optimize database performance and maintain data integrity across SQL and NoSQL systems including DynamoDB.
• Lead and mentor a team of data engineers on best practices and technical troubleshooting.
• Manage monitoring and alerting systems using AWS CloudWatch, Splunk, and New Relic.
• Participate in production support and incident resolution, including after-hours or weekend requirements.

Required Skills

• 10+ years of data engineering experience.
• Extensive experience with AWS technologies including EMR, Glue, S3, Lambda, and CloudWatch.
• Strong programming proficiency in Python, Scala, and Java.
• Hands-on experience with Spark and Databricks.
• Expertise in SQL and Bash scripting.
• Experience with Snowflake data warehousing.
• Hands-on experience with DynamoDB and other NoSQL databases.
• Solid understanding of Agile engineering practices and JIRA.

Preferred Skills

• Familiarity with Kafka for real-time data streaming.
• Experience with Airflow for orchestrating complex workflows.
• Knowledge of open table formats such as Delta, Hudi, or Iceberg.
• Experience with monitoring tools such as Splunk and New Relic.

Key Skills

Education

Any Gradute