Gcp Developer (Remote)

Job Title: Senior Google Cloud Data Engineer (with API DevelopmentExperience)

Location: Remote

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Gcp Developer | Cymetrix | India

Job Title: Senior Google Cloud Data Engineer (with API Development Experience)

Location: Remote

• Job Type: Full-time/Freelancer

“Must have skills:

1. GCP – GCS, PubSub, Dataflow or DataProc, Bigquery, Airflow/Composer, Python(preferred)/Java

2. ETL on GCP Cloud – Build pipelines (Python/Java) + Scripting, Best Practices, Challenges

3. Knowledge of Batch and Streaming data ingestion, build End to Data pipelines on GCP

4. Knowledge of Databases (SQL, NoSQL), On-Premise and On-Cloud, SQL vs No SQL, Types of No-SQL DB (at least 2 databases)

5. Data Warehouse concepts – Beginner to Intermediate level”

Required Skills & Qualifications:

● Experience with Google Cloud Platform (GCP): Proficiency with GCP services, including

BigQuery, Cloud Storage, Dataflow, Pub/Sub, Cloud Functions, Cloud Composer

(Airflow), and Kubernetes Engine (GKE).

● Data Engineering & Transformation Expertise: Strong experience in building and

optimizing ETL/ELT pipelines, performing data cleansing, transformation, and normalization

tasks. Expertise in working with large datasets and ensuring that data is structured for

efficient analysis and reporting.

● API Development: Extensive experience in designing, developing, and maintaining RESTful

APIs. Familiarity with OAuth, JWT, and best practices in API versioning, documentation, and

security.

● Distributed Systems & Cloud Architecture: Knowledge of distributed systems,

microservices, and cloud-native application architecture. Hands-on experience with cloud

infrastructure management (compute, storage, networking).

● Data Modeling & Data Warehousing: Experience in building and maintaining data

warehouses, designing optimized schemas, and working with data lakes or large-scale data

storage solutions.

● Automation & Orchestration: Familiarity with workflow orchestration tools such as Airflow

and automation frameworks. Experience in automating cloud infrastructure deployments

using Terraform, Cloud Deployment Manager, or similar tools.

● Collaboration Tools: Comfortable working with Git, Jira, and Confluence for version control,

issue tracking, and documentation.

● Problem Solving: Strong analytical skills, with a proven ability to troubleshoot complex

issues and deliver effective solutions.

Preferred Qualifications:

● Cloud Certifications: Google Cloud Professional Data Engineer or Professional Cloud

Architect certification is a plus.

● Security & Compliance: Understanding of data security best practices, compliance

frameworks (e.g., GDPR, CCPA), and encryption techniques in cloud environments.

● CI/CD Pipeline Experience: Experience setting up continuous integration and deployment

pipelines for data solutions and APIs.

● Data Pipeline Development & Transformation: Design, develop, and maintain efficient and

scalable data pipelines using Google Cloud technologies such as BigQuery, Cloud

Dataflow, Cloud Composer (Airflow), Data Fusion, Pub/Sub, Cloud Storage, and Dataproc.

Transform raw data into actionable insights by applying data cleansing, enrichment,

normalization, and aggregation techniques.

● Data Transformation & Processing: Lead complex data transformation projects, including

ETL/ELT processes, data validation, and enrichment. Optimize transformation logic for

performance, scalability, and maintainability, ensuring that data is structured in a way that

facilitates easy analysis and reporting.

● API Development & Integration: Develop and maintain RESTful APIs for data access and

integration with internal and external systems, ensuring high availability and low latency.

Ensure that APIs are secure, well-documented, and easy to integrate.

● Cloud Infrastructure Management: Implement and manage data infrastructure on Google

Cloud, optimizing for performance, scalability, and cost-efficiency. Leverage Google

Kubernetes Engine (GKE) and Cloud Functions to deploy containerized services and

event-driven functions.

● Collaboration & Mentorship: Work closely with cross-functional teams to understand data

needs and deliver solutions that address business requirements. Mentor junior engineers,

sharing your expertise in best practices for cloud data engineering, API design, and data

transformation.

● Documentation & Reporting: Maintain thorough documentation for data pipelines,

infrastructure, data transformations, and APIs. Provide regular updates to stakeholders on

project status, challenges, and outcomes.

Required Skills & Qualifications:

● Experience with Google Cloud Platform (GCP): Proficiency with GCP services, including

BigQuery, Cloud Storage, Dataflow, Pub/Sub, Cloud Functions, Cloud Composer

(Airflow), and Kubernetes Engine (GKE).

● Data Engineering & Transformation Expertise: Strong experience in building and

optimizing ETL/ELT pipelines, performing data cleansing, transformation, and normalization

tasks. Expertise in working with large datasets and ensuring that data is structured for

efficient analysis and reporting.

● API Development: Extensive experience in designing, developing, and maintaining RESTful

APIs. Familiarity with OAuth, JWT, and best practices in API versioning, documentation, and

security.

● Distributed Systems & Cloud Architecture: Knowledge of distributed systems,

microservices, and cloud-native application architecture. Hands-on experience with cloud

infrastructure management (compute, storage, networking).

● Data Modeling & Data Warehousing: Experience in building and maintaining data

warehouses, designing optimized schemas, and working with data lakes or large-scale data

storage solutions.

● Automation & Orchestration: Familiarity with workflow orchestration tools such as Airflow

and automation frameworks. Experience in automating cloud infrastructure deployments

using Terraform, Cloud Deployment Manager, or similar tools.

● Collaboration Tools: Comfortable working with Git, Jira, and Confluence for version control,

issue tracking, and documentation.

● Problem Solving: Strong analytical skills, with a proven ability to troubleshoot complex

issues and deliver effective solutions.

Preferred Qualifications:

● Cloud Certifications: Google Cloud Professional Data Engineer or Professional Cloud

Architect certification is a plus.

● Security & Compliance: Understanding of data security best practices, compliance

frameworks (e.g., GDPR, CCPA), and encryption techniques in cloud environments.

● CI/CD Pipeline Experience: Experience setting up continuous integration and deployment

pipelines for data solutions and APIs.

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