Data Architect

1 week ago

Bangalore, India Sourcebae Full time
Job Title: GCP Data Architect Location: Experience: 10–12 Years

We are seeking a highly skilled GCP Data Architect to join our Procurement Services – Data & Strategy team. The ideal candidate will have a strong foundation in data strategy and architecture, capable of assessing the current data landscape, recommending improvements, and driving alignment between data engineering and business analytics teams. This role is critical in shaping a scalable and efficient data model to enable advanced procurement analytics and reporting.

Conduct a thorough assessment of the current procurement data architecture to identify gaps, inefficiencies, and opportunities for improvement.
Design and propose enhancements to data models that align with procurement objectives and reporting requirements.
Collaborate with data engineers to guide the implementation of architectural changes and improvements to data pipelines.
Partner with BI developers and business stakeholders to understand data consumption needs and ensure effective delivery.
Provide a strategic, end-to-end view of the procurement data ecosystem, ensuring alignment with long-term business goals.
Act as a bridge between technical and functional teams, ensuring clarity, cohesion, and data-driven decision-making.
Technical Skills & Experience:
Hands-on experience with Google Cloud Platform (GCP), particularly GCP Data Lakes.
Expertise in BigQuery for data querying and structuring.
Proficiency in DBT (Data Build Tool) for modular SQL-based data transformations.
Experience with ELT architectures and large-scale data pipelines.
Strong understanding of data modeling concepts: normalization, star/snowflake schemas, dimensional modeling.
Experience in assessing and improving data quality, lineage, and governance.
Familiarity with batch and streaming data processing patterns.
Experience designing scalable and maintainable data pipelines aligned with governance principles.
Integration experience with Oracle Autonomous Database (ATP/ADW), Object Storage, File systems, REST APIs, and on-prem databases.
Built robust data ingestion pipelines for structured and semi-structured data (JSON, CSV, XML, Parquet).
Skilled in logical and physical data modeling, schema design, and metadata management.
SQL (advanced), PL/SQL – for data manipulation, ETL logic, and performance tuning.
Python – for custom data transformations and orchestration scripts.
Shell/Bash scripting – automating data pipeline deployment and monitoring.
Proven ability to translate business needs into scalable data architecture solutions.

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