Hybrid – 3 days on site
Key Responsibilities
* Data Pipeline Development
* Design and implement robust ETL/ELT pipelines using GCP services like Dataflow, Dataproc, Cloud Composer, and Data Fusion.
* Automate data ingestion from diverse sources (APIs, databases, flat files) into BigQuery and Cloud Storage
Data Modelling & Warehousing
* Develop and maintain data models and marts in BigQuery.
* Optimize data storage and retrieval for performance and cost efficiency.
Security & Compliance
* Implement GCP security best practices including IAM, VPC Service Controls, and encryption.
* Ensure compliance with GDPR, HIPAA, and other regulatory standards.
Monitoring & Optimization
* Set up monitoring and alerting using Stackdriver.
* Create custom log metrics and dashboards for pipeline health and performance
Collaboration & Support
* Work closely with cross-functional teams to gather requirements and deliver data solutions.
* Provide architectural guidance and support for cloud migration and modernization initiatives
Skillset
Technical Skills
* Languages: Python, SQL, Java (optional)
* GCP Services: BigQuery, Dataflow, Dataproc, Cloud Storage, Cloud SQL, Cloud Functions, Composer (Airflow), App Engine
* Tools: GitHub, Jenkins, Terraform, DBT, Apache Beam
* Databases: Oracle, Postgres, MySQL, Snowflake (basic)
* Orchestration: Airflow, Cloud Composer
* Monitoring: Stackdriver, Logging & Alerting
Certifications
* Google Cloud Certified – Professional Data Engineer
* Google Cloud Certified – Associate Cloud Engineer
* Google Cloud Certified – Professional Cloud Architect (optional)
Soft Skills
* Strong analytical and problem-solving skills
* Excellent communication and stakeholder management
* Ability to work in Agile environments and manage multiple priorities
Experience Requirements
* Extensive experience in data engineering
* Strong hands‑on experience with GCP
* Experience in cloud migration and real‑time data processing is a plus
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