Role: Data Architect

Experience: 12+ Years

Employment Type: Full-Time

Mode-Hybrid

Job Summary

We are looking for an experienced Data Architect to design, govern, and implement enterprise-scale data architecture, data platforms, data warehouses, data lakes/lakehouses, and analytics ecosystems supporting BI, Advanced Analytics, AI/ML, Generative AI, and digital transformation initiatives.

The ideal candidate should have strong expertise in Data Modelling, Data Warehousing, ETL/ELT, Cloud Data Platforms, Data Governance, Data Integration, SQL, and modern Data Engineering.

The role involves working closely with business stakeholders, Enterprise Architects, Data Engineers, Analysts, and AI/ML teams to build scalable, secure, highly available, and high-performing data solutions.

Key Responsibilities

- Define and maintain enterprise Data Architecture strategy, standards, and roadmap.
- Design conceptual, logical, and physical data models.
- Architect Data Warehouses, Data Lakes, and Lakehouse solutions.
- Design and optimize ETL/ELT pipelines, data integration frameworks, and real-time data processing architectures.
- Establish Data Governance, Metadata Management, MDM, Data Quality, Data Lineage, and Security standards.
- Design cloud-based data platforms using AWS, Azure, or GCP.
- Provide architecture guidance for BI, Analytics, AI/ML, and Generative AI initiatives.
- Evaluate data technologies, storage solutions, integration tools, and performance optimization strategies.
- Ensure compliance with applicable security, privacy, and regulatory standards such as GDPR, HIPAA, and ISO.
- Lead architecture reviews, technical design discussions, and governance forums.




- Mentor Data Engineers and Developers on architecture best practices, design patterns, and performance tuning.
- Prepare and maintain architecture documents, data dictionaries, standards, and solution blueprints.

Mandatory Skills

- 12+ years of experience in Data Architecture, Data Engineering, or Enterprise Data Management.
- Strong expertise in:
- Data Modelling – ER, Dimensional, Star Schema, Snowflake Schema
- Data Warehousing
- ETL/ELT Architecture
- SQL and Database Design
- Data Integration Patterns
- Data Governance and Data Quality
- Strong hands-on experience with at least one major cloud platform:

AWS: Redshift, Glue, Athena, S3, Lake Formation, EMR Azure: Synapse, Data Factory, ADLS, Databricks

GCP: BigQuery, Dataflow, Dataproc, Cloud Storage

- Experience with relational and NoSQL databases such as PostgreSQL, SQL Server, Oracle, MongoDB, Cassandra, or DynamoDB.
- Strong knowledge of Spark / PySpark and distributed data processing.
- Solid SQL skills and familiarity with Python or Scala.
- Experience designing high-volume, highly available, and scalable enterprise data platforms.
- Strong stakeholder management, communication, architecture, and problem-solving skills.

Preferred Skills

- Databricks
- Snowflake
- Delta Lake
- Apache Kafka
- Apache Airflow
- MLOps and Feature Stores
- AI/ML Data Platform Architecture
- Generative AI
- Vector Databases
- Semantic Layers
- RAG (Retrieval-Augmented Generation)
- Terraform / CloudFormation / ARM Templates
- CI/CD for Data Platforms

Education Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Science, Engineering, or a related field.

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