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Data Architect

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Hybrid

Data Architect

Spark Tech Wave Innovation

Data Architect

Skills

Google Cloud PlatformSQL QueriesBig DataMongoDBData EngineeringPythonData SciencePostgreSQLMySQLCassandraKafkaSnowflakeGoogle BigQueryAmazon RedshiftMicrosoft Azure Cosmos DBDatabricksData AnalysisAWSLinuxKubernetesOracleHadoopComplianceAzure

15 days ago

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Important information


Contract type:

Permanent

Location:

India

Work mode:

Hybrid

Published on:

6 October 2026

What they need


Data Architect Data Architecture | Cloud | Data Modeling | Big Data

Company: Spark Techwave InnovationZ Pvt Ltd
Job Type: Full-Time
Experience: 7–12 Years
Location: Chennai / Remote / Hybrid
Department: Data & Analytics

Job Summary

Spark Techwave InnovationZ Pvt Ltd is looking for an experienced Data Architect to design and implement scalable, secure, and high-performance data architecture solutions.

The ideal candidate should have strong experience in data architecture, data modeling, database design, data integration, cloud data platforms, data warehousing, and Big Data technologies.

The Data Architect will work closely with engineering, analytics, business, security, and technology teams to define data strategies and architecture standards that support business and analytical requirements.

Key Responsibilities

  • Design scalable and reliable enterprise data architectures.
  • Define data architecture strategies, standards, principles, and best practices.
  • Design conceptual, logical, and physical data models.
  • Define data flows, data domains, integration patterns, and storage strategies.
  • Design modern data warehouse, data lake, and lakehouse architectures.
  • Evaluate and recommend appropriate databases, data platforms, and technologies.
  • Design batch and real-time data integration architectures.
  • Define architecture for structured, semi-structured, and unstructured data.
  • Collaborate with Data Engineers to implement architectural solutions.
  • Work with Data Scientists, Data Analysts, BI teams, and business stakeholders to understand data requirements.
  • Ensure data architecture supports scalability, availability, performance, and reliability.
  • Define data security, privacy, access-control, and governance standards.
  • Establish data quality and metadata management practices.
  • Review existing data architectures and identify opportunities for modernization and optimization.
  • Evaluate technology solutions and conduct proof-of-concepts where required.
  • Create architecture diagrams, technical documentation, and design specifications.
  • Provide technical guidance and mentorship to Data Engineers and other technical teams.
  • Ensure architecture decisions align with enterprise technology and business objectives.

Required Skills

Data Architecture

Strong knowledge of:

  • Enterprise Data Architecture
  • Data Architecture Principles
  • Data Modeling
  • Data Integration
  • Data Warehousing
  • Data Lakes
  • Lakehouse Architecture
  • Data Governance
  • Data Quality
  • Metadata Management
  • Master Data Management

Data Modeling

Hands-on experience with:

  • Conceptual Data Models
  • Logical Data Models
  • Physical Data Models
  • Dimensional Modeling
  • Star Schema
  • Snowflake Schema
  • Normalization / Denormalization
  • Fact and Dimension Tables
  • Slowly Changing Dimensions (SCD)

Databases

Strong knowledge of relational databases such as:

  • PostgreSQL
  • MySQL
  • SQL Server
  • Oracle

Experience with NoSQL databases is an advantage:

  • MongoDB
  • Cassandra
  • DynamoDB
  • Cosmos DB

Cloud Data Architecture

Hands-on experience with one or more cloud platforms:

AWS

  • S3
  • Redshift
  • Glue
  • EMR
  • Athena
  • Lake Formation

Azure

  • Azure Data Lake Storage
  • Azure Data Factory
  • Azure Synapse Analytics
  • Azure Databricks
  • Microsoft Purview

Google Cloud

  • BigQuery
  • Cloud Storage
  • Dataproc
  • Dataflow
  • Dataplex

Big Data Technologies

Experience with one or more:

  • Apache Spark
  • Hadoop
  • Kafka
  • Databricks
  • Hive
  • Distributed data processing

Data Integration

Strong understanding of:

  • ETL / ELT
  • Batch processing
  • Real-time data integration
  • API-based integration
  • Data ingestion
  • Change Data Capture (CDC)
  • Event-driven architectures
  • Data pipeline architecture

Data Warehousing

Experience designing:

  • Enterprise Data Warehouses
  • Data Marts
  • Cloud Data Warehouses
  • Data Lakes
  • Lakehouses
  • Analytical data platforms

Knowledge of platforms such as:

  • Snowflake
  • Amazon Redshift
  • Azure Synapse
  • Google BigQuery
  • Databricks

Data Governance & Security

Understanding of:

  • Data Governance
  • Data Cataloging
  • Data Lineage
  • Data Classification
  • Data Quality
  • Role-Based Access Control
  • Data Privacy
  • Encryption
  • Regulatory and compliance requirements

Experience with tools such as Collibra, Informatica, Microsoft Purview, Alation, or similar platforms is an advantage.

Programming & Technical Skills

Good understanding of:

  • SQL
  • Python
  • Data processing frameworks
  • REST APIs
  • Git
  • Linux

Knowledge of infrastructure-as-code, CI/CD, containers, or Kubernetes is an advantage.

Architecture & Design

Experience with:

  • Architecture diagrams
  • Solution design
  • Technology evaluation
  • Proof of Concepts
  • Architecture documentation
  • Performance and scalability planning
  • High availability and disaster recovery
  • Cost optimization

Education

Bachelor's or Master's degree in:

  • Computer Science
  • Information Technology
  • Engineering
  • Data Science
  • Mathematics
  • Or a related technical field.

Experience

7–12 years of overall experience in Data Engineering, Data Architecture, Database Architecture, Big Data, or related fields.

Candidates should have significant hands-on experience designing and implementing enterprise-scale data solutions.

Preferred Candidate Profile

The ideal candidate should have experience in:

  • Enterprise Data Architecture
  • Cloud Data Architecture
  • Data Modeling
  • Data Warehousing
  • Data Lakes / Lakehouse
  • Big Data
  • Data Integration
  • Data Governance
  • Data Security
  • Cloud platforms
  • Architecture design and technical leadership

Strong communication and stakeholder-management skills are required.

Key Skills for Naukri

Data Architect, Data Architecture, Enterprise Data Architecture, Data Modeling, Data Warehouse, Data Lake, Lakehouse, Cloud Data Architecture, AWS, Azure, GCP, Snowflake, Databricks, SQL, ETL, ELT, Big Data, Apache Spark, Kafka, Data Governance, Data Integration, Data Security, Data Quality, Data Warehousing, Dimensional Modeling

Interested candidates can apply with their updated resume at [email protected]

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