Senior Data Architect

Job Title: Senior Data Architect/ Senior Data Modeler

Job Type: Permanent

Experience: 8+ years

Location: Bangalore (Hybrid)

Start: ASAP

Job Description:-

The Senior Data Architect / Senior Data Modeler is responsible for designing, optimizing, and governing enterprise data architecture and data models that support analytics, operations, and digital transformation initiatives. This role partners closely with engineering, product, analytics, and business teams to ensure data is structured, scalable, high-quality, and aligned with organizational strategy.

Key Responsibilities

Data Architecture & Design

• Define and maintain the enterprise data architecture, including conceptual, logical, and physical data models.
• Design scalable and efficient data structures for OLTP, OLAP, and real-time systems.
• Lead the design of data platforms (cloud and on‑prem) such as SQL Server, Oracle, Databricks, data lakes such as AWS and Azure Lakehouse, data warehouses, and data integration frameworks such as Data sync, Replication and CDC.
• Establish data modeling standards, patterns, and best practices around microservice architecture, data warehousing and ML models

Data Modeling

• Develop and maintain high‑quality data models using dimensional, relational, and NoSQL modeling techniques.
• Translate business requirements into robust models supporting analytics, reporting, machine learning, and operational workloads.
• Review and optimize existing data models for performance, scalability, and cost efficiency.
• Create metadata, data dictionaries, and lineage documentation.

Data Governance & Quality

• Define and enforce data governance practices in collaboration with data stewardship teams.
• Ensure data accuracy, consistency, security, and compliance with relevant standards (e.g., GDPR, HIPAA, SOC2).
• Collaborate with engineering teams to implement data quality frameworks and monitoring.
• Data Cleansing & Hygiene: Ensure high input quality to prevent flawed model training ("garbage in, garbage out").
• AI Compliance & Security: Implement strict access controls and monitor data usage regulations for sensitive AI workloads.
• Metadata Management: Standardize data lineage tracking so model outputs remain explainable and auditable.

Core AI & Data Infrastructure Skills

• Vector Databases: Manage specialized storage systems like Pinecone, Milvus, or Qdrant for embedding data.
• RAG Systems: Design pipelines that connect enterprise data stores securely to foundational models.
• MLOps & Feature Stores: Understand how data feeds ML models via platforms like Feast or AWS SageMaker.
• Distributed Computing: Process heavy AI training loads using Apache Spark or Ray

Collaboration & Leadership

• Partner with stakeholders to understand business processes, data needs, and analytical goals.
• Provide thought leadership on data strategy, architecture modernization, and emerging technologies.
• Mentor data engineers, data modelers, and analysts; conduct design reviews and architectural assessments.
• Drive adoption of master data management (MDM), data cataloging, and metadata management practices.

Technical Expertise

• Work closely with engineering teams on data pipeline design, ETL/ELT strategies, and cloud platform implementation.
• Lead evaluations and selection of data technologies, modeling tools, and architecture patterns.
• Optimize database performance, indexing strategies, and partitioning schemes.

Required Qualifications

• 8+ years of experience as a Data Architect, Data Modeler, or related data engineering/architecture role.
• Expert-level knowledge of data modeling (3NF, star schema, snowflake, data vault, NoSQL structures).
• Strong experience with modern cloud data platforms (e.g., Azure, Databricks, AWS Redshift/Glue, Google BigQuery).
• Proficiency with data modeling tools (e.g., ERwin, ER/Studio, dbt, PowerDesigner).
• Deep understanding of SQL and performance optimization.
• Experience designing enterprise‑scale data architecture and data integration solutions.