Roles and Responsibilities:
About the Role:
We are looking for a Data Architect with a strong background in data engineering & cloud data platforms. The ideal candidate will design and implement scalable data architectures that power enterprise analytics, AI/ML, and GenAI solutions — ensuring data availability, quality, and governance across the organization.
Key Responsibilities:
Data Architecture & Strategy
Design and implement enterprise-grade data architecture frameworks supporting analytics, AI/ML, and GenAI use cases.
Define and maintain data models, pipelines, and integrations across structured, semi-structured, and unstructured sources.
Partner with business and technology stakeholders to align data strategy with organizational goals.
Establish and enforce best practices in data governance, metadata management, and data lineage.
Data Engineering:
Architect and optimize large-scale ETL/ELT pipelines using tools like Databricks etc.
Work closely with data engineers to build reliable, real-time, and batch data pipelines.
Implement scalable data storage and compute solutions across AWS / Azure / GCP.
Optimize performance, cost, and scalability of data platforms.
Partner with AI/ML engineers to prepare, curate, and manage training data for GenAI applications.
Implement data pipelines for prompt engineering, vector databases, and model fine-tuning.
Ensure data security, privacy, and compliance in AI data processing.
Required Skills & Experience:
10+ years of experience in Data Architecture / Data Engineering roles.
Proven expertise in data modeling, ETL/ELT design, and cloud-based data solutions (AWS Redshift, Snowflake, BigQuery, or Synapse).
Hands-on experience with data pipeline orchestration tools (Airflow, DBT, Azure Data Factory, etc.).
Proficiency in Python, SQL, and Spark for data processing and integration.
Experience with API integrations and data APIs for AI systems.
Excellent communication and stakeholder management skills.
Location:
Experience: 10 – 14 Yrs.
