Senior Data Engineer

Okta Okta · Enterprise · Bangalore, India · Product & Platform Data-693

Okta is seeking a Senior Data Engineer for their Auth0 Data Engineering Team in Bengaluru. This role focuses on building and operating critical data pipelines and infrastructure, managing data onboarding, and developing scalable data solutions using tools like Snowflake, dbt, and Airflow. The ideal candidate will have 5+ years of experience in large-scale data systems, strong SQL and Python skills, and cloud environment experience.

What you'd actually do

  1. Own and operate our critical data pipelines and infrastructure, participating in the team's support rotation to ensure high availability and business continuity.
  2. Lead troubleshooting efforts to fix complex pipeline or infrastructure issues, demonstrating a willingness to go beyond the direct scope of the team to find resolutions.
  3. Manage the data onboarding lifecycle, working with stakeholders to integrate new internal and external data sources into our platform using our suite of tools.
  4. Develop and deploy robust, scalable data solutions using modern tools and technologies like Snowflake, dbt, Airflow, and Terraform.
  5. Continuously learn and advocate for modern technologies and best practices to improve data delivery and engineering efficiency.

Skills

Required

  • SQL
  • Python
  • Data Pipelines
  • Cloud Environment (AWS preferred)
  • Snowflake
  • dbt
  • Airflow
  • Terraform
  • Data Ingestion
  • Streaming
  • Event-driven architecture
  • Data Security
  • Data Privacy
  • Data Modeling

Nice to have

  • Snowpark
  • Containerization
  • Orchestration
  • Kubernetes
  • Identity Access & Management (IAM)
  • REST
  • gRPC

What the JD emphasized

  • 5+ years of software development experience, with at least 3+ years working on large-scale data systems
  • Strong proficiency in SQL for data manipulation and Python for data pipeline development
  • Hands-on experience building and operating data pipelines in a cloud environment (AWS preferred)
  • Experience with data ingestion, streaming, and event-driven architecture (e.g., Kafka, CDC, Snowpipe)
  • A strong understanding of data modeling principles
  • data security best practices