Back to jobs

GCP Data Architect

Location not identified

Pay
Salary not listed in the saved posting
Work setup
Remote stated — work setup source
This is a remote position. Scope:
Read the full posting
Employment
Unconfirmed
Apply at Kanini

What you’ll work on

Full posting
  • Lead architecture decisions for GCP data platforms.

  • Ensure scalability, security, and performance across data platforms and pipelines.

  • Define standards for DevOps/DataOps practices, including CI/CD, monitoring, and cost optimization.

From the employer’s posting
Key Responsibilities Lead architecture decisions for GCP data platforms. Ensure scalability, security, and performance across data platforms and pipelines.
Lead architecture decisions for GCP data platforms. Ensure scalability, security, and performance across data platforms and pipelines. Define standards for DevOps/DataOps practices, including CI/CD, monitoring, and cost optimization.
Ensure scalability, security, and performance across data platforms and pipelines. Define standards for DevOps/DataOps practices, including CI/CD, monitoring, and cost optimization. Drive adoption of modern data architecture patterns (Data Mesh, Lakehouse, etc.).

What you’ll bring

All qualifications

Core experience

  • 8–12+ years of experience in data engineering, data architecture, or enterprise data platform roles.
  • Experience with streaming and event-driven architectures (Kafka, Pub/Sub, Kinesis).
  • Strong experience designing enterprise data architectures, data models, and integration frameworks.
  • Hands-on knowledge of modern data platforms (Snowflake, BigQuery, Redshift, Databricks).
  • Deep knowledge of GCP cloud data platforms ( GCP) and services such as Google Cloud Dataflow.
  • Experience implementing Data Lake, Lakehouse, or Data Mesh architectures.
Qualification wording
8–12+ years of experience in data engineering, data architecture, or enterprise data platform roles.
Experience with streaming and event-driven architectures (Kafka, Pub/Sub, Kinesis).
Strong experience designing enterprise data architectures, data models, and integration frameworks.
Hands-on knowledge of modern data platforms (Snowflake, BigQuery, Redshift, Databricks).
Deep knowledge of GCP cloud data platforms ( GCP) and services such as Google Cloud Dataflow.
Experience implementing Data Lake, Lakehouse, or Data Mesh architectures.

Tools in this posting

  • Python
  • SQL
  • BigQuery
  • Google Cloud (GCP)
  • Kafka
  • Redshift
  • Snowflake
  • Databricks
Source — Tool mentions in context
- Deep knowledge of GCP cloud data platforms ( GCP) and services such as Google Cloud Dataflow. - Proficient in SQL, Python, and scripting for data manipulation and automation - Experience with ETL/ELT tools (Informatica, Talend, SSIS, etc.) from an architectural/design perspective.
- Experience with streaming and event-driven architectures (Kafka, Pub/Sub, Kinesis). - Hands-on knowledge of modern data platforms (Snowflake, BigQuery, Redshift, Databricks). - Experience implementing Data Lake, Lakehouse, or Data Mesh architectures.
- Strong experience designing enterprise data architectures, data models, and integration frameworks. - Deep knowledge of GCP cloud data platforms ( GCP) and services such as Google Cloud Dataflow. - Proficient in SQL, Python, and scripting for data manipulation and automation
- Architect robust data integration frameworks across internal systems, APIs, SaaS platforms, and cloud services. - Define standards for batch and real-time data processing, including event-driven architectures and streaming platforms (e.g., Kafka, Pub/Sub). - Guide the design of ETL/ELT pipelines, ensuring scalability, reusability, and performance (execution may be handled by engineering teams).
Preferred - Experience with streaming and event-driven architectures (Kafka, Pub/Sub, Kinesis). - Hands-on knowledge of modern data platforms (Snowflake, BigQuery, Redshift, Databricks).

Job description

View original posting ↗

This is a remote position.


Scope:

We are seeking a strategic and technically strong Data Architect to define, design, and govern enterprise data architecture and integration frameworks. This role is responsible for establishing scalable, secure, and high-performing data ecosystems that enable advanced analytics, business intelligence, and operational excellence.

The ideal candidate will bring deep expertise in data modeling, architecture patterns, integration strategies, and data governance, along with the ability to translate business needs into cohesive data solutions across complex, hybrid environments.

 

Key Responsibilities
  • Lead architecture decisions for GCP data platforms.
  • Ensure scalability, security, and performance across data platforms and pipelines.
  • Define standards for DevOps/DataOps practices, including CI/CD, monitoring, and cost optimization.
  • Drive adoption of modern data architecture patterns (Data Mesh, Lakehouse, etc.).
  • Architect robust data integration frameworks across internal systems, APIs, SaaS platforms, and cloud services.
  • Define standards for batch and real-time data processing, including event-driven architectures and streaming platforms (e.g., Kafka, Pub/Sub).
  • Guide the design of ETL/ELT pipelines, ensuring scalability, reusability, and performance (execution may be handled by engineering teams).
  • Define and enforce data governance frameworks, including data quality, stewardship, lineage, and metadata management.
  • Establish enterprise standards for data validation, consistency, and observability.
  • Partner with stakeholders to implement data catalogs, lineage tracking, and master data management (MDM) strategies.
  • Ensure compliance with data privacy and regulatory requirements (e.g., HIPAA, GDPR).
  • Collaborate with data engineers, data scientists, business leaders, and application teams to align architecture with business goals.
  • Provide architectural guidance and oversight for data-related initiatives and projects.
  • Mentor engineering teams on best practices in data architecture, modeling, and integration design.
  • Act as a key advisor on data strategy and decision-making across the organization.

 

QUALIFICATIONS
Required
  • 8–12+ years of experience in data engineering, data architecture, or enterprise data platform roles.
  • Strong experience designing enterprise data architectures, data models, and integration frameworks.
  • Deep knowledge of GCP cloud data platforms ( GCP) and services such as Google Cloud Dataflow.
  • Proficient in SQL, Python, and scripting for data manipulation and automation
  • Experience with ETL/ELT tools (Informatica, Talend, SSIS, etc.) from an architectural/design perspective.
  • Strong understanding of APIs, microservices, and distributed systems.


Preferred
  • Experience with streaming and event-driven architectures (Kafka, Pub/Sub, Kinesis).
  • Hands-on knowledge of modern data platforms (Snowflake, BigQuery, Redshift, Databricks).
  • Experience implementing Data Lake, Lakehouse, or Data Mesh architectures.
  • Familiarity with data governance tools, data catalogs, and metadata management solutions.
  • Industry experience in healthcare, fintech, or e-commerce environments.

 



Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the salary range before committing time to the process.

Complete your application on kanini.zohorecruit.in. The employer’s form will show what is required.

Already applied? Track this application

Source & posting history

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay

No pay amount identified in the saved description.

Location & working pattern

Location not supplied.

This is a remote position. Scope:
More source context
We are seeking a strategic and technically strong Data Architect to define, design, and govern enterprise data architecture and integration frameworks. This role is responsible for establishing scalable, secure, and high-performing data ecosystems that enable advanced analytics, business intelligence, and operational excellence. The ideal candidate will bring deep expertise in data modeling, architecture patterns, integration strategies, and data governance, along with the ability to translate business needs into cohesive data solutions across complex, hybrid environments. Key Responsibilities
Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

Status in our records
Active
First seen by us
Jul 19, 2026
Recorded sightings
26
Last seen by us
Oct 2, 2026

These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.

Report an error

See how this role fits your experience

Add your resume to compare the role’s scope, tools and requirements with your experience.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.