• Data Architecture: Design, build, and optimize GCP-based data pipelines (streaming/Batch) using services like BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Composer. Architect data lakes/warehouses for structured and unstructured data.

• Pipeline Development: Implement ETL/ELT workflows and integrate data from heterogeneous sources (APIs, databases, streaming platforms) using tools like Spark, Apache Beam, DBT, and Kafka.

• GCP Expertise: Proficiency in BigQuery, Dataflow, Dataproc, Cloud SQL, Pub/Sub , logging and monitoring.

• Programming: Strong coding skills in Python, SQL,Java and familiarity with Apache Spark

• DevOps & IaC: Experience with Terraform, Kubernetes, and CI/CD pipelines for infrastructure automation

• Data Modeling: Working Knowledge of relational, NoSQL (Bigtable, Firestore), and Vector databases.

• Governance & Compliance: Enforce data security, encryption, and governance standards (GDPR, CCPA) using GCP tools like Cloud KMS and IAM policies

• Collaboration: Partner with data scientists, DevOps, and business teams to deploy AI/ML models, BI dashboards (PowerBI ,Looker,Qlik), and real-time analytics solutions

• Operational Excellence: Automate CI/CD pipelines, monitor system performance, and troubleshoot issues using Terraform, Jenkins, and GCP monitoring tools

• Develop data engineering pipelines, frameworks focused on modularity & Data craftsmanship in GCP.

• Hands an individual contributor for Log data management, analytics, integration with observability and AIOps platforms.

• Democratize “Data as a service" API for all interfacing systems.

• As a senior engineer ensure the data pipelines built by teams are robust, scalable and meets the highest standards.

• Execute data governance and data quality projects.

• Serve as role model for data engineering experts with strong emphasis on bias towards action.

Requisition ID : 42563