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 :

3–6 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.