GCP Data Engineer(Only Immediate)

About the role-

As a Software Engineer II - Data, you will contribute to the design and development of data systems including pipelines, APIs, analytics, AI and machine learning at scale. You'll be a core part of our Data Products team, building and maintaining production-grade pipelines and platform components that power business and product outcomes. This role emphasizes hands-on development, reliability, and team collaboration.

Role requires:

• A proactive and collaborative approach to problem-solving, with a mindset focused on outcomes, learning, and iteration.
• The ability to manage multiple priorities or projects simultaneously, while meeting deadlines and maintaining high technical standards.
• Comfort operating within modern cloud-native architectures and tooling.
• Commitment to writing clean, testable, and maintainable code.
• An understanding of how your work contributes to broader team and business goals.
• Willingness to ask questions, challenge assumptions, and share ideas.

Experience & Technical Requirements:

• 36 years of development experience, with production systems in cloud environments.
• Proficient in Python and/or Golang, and SQL for data processing, transformation, and orchestration tasks.
• Experience with at least one modern cloud platform (e.g., GCP, AWS, or Azure).
• Experience developing REST or GraphQL APIs and internal data access layers.
• Experience building and maintaining ETL/ELT pipelines or API-driven data services.
• Experience with source control (e.g., Git), automated testing, and CI/CD practices.
• Exposure to orchestration tooling such as n8n, Cloud scheduler, Airflow, Step Functions, or similar.
• Understanding of data modeling concepts and cloud warehousing (e.g. Databricks, BigQuery, Snowflake or other).
• Familiarity with Kafka, Pub/Sub, or other event-based systems.
• Awareness of data quality, observability, and governance principles in engineering contexts.
• Strong written and verbal communication skills, with an ability to share context with both technical peers and cross-functional partners.
• Experience working with containerized environments (e.g., Docker, Kubernetes).
• Exposure to infrastructure-as-code, especially for deploying and managing data workflows.
• Hands-on use of BI tools like Looker or Tableau
• A growth mindset and interest in mentoring junior peers or learning from senior engineers.