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Data Architect

Data Architect

Bigtapp

5 - 15 years

7 - 17 Lacs

Hyderabad Chennai Bengaluru

Posted:1 month ago| Platform:

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Skills Required

Architecture Data modeling TOGAF Data structures Informatica Oracle Virtualization SQL Data architecture Python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Job Title: Data ArchitectLocation: Chennai,Bangalore,HyderabadExperience: 5 - 15 Years

Job Title: Hyderabad, Chennai & Bangalore

Job Summary

We are seeking a highly experienced and strategic Data Architect to lead the design and implementation of robust data architecture solutions. The ideal candidate will have a deep understanding of data modelling, governance, integration, and analytics platforms. As a Data Architect, you will play a crucial role in shaping the data landscape across the organization, ensuring data availability, consistency, security, and quality.

Mandatory Skills

Enterprise data architecture and modeling

Cloud data platforms (Azure, AWS, GCP)

Data warehousing and lakehouse architecture

Data governance and compliance frameworks

ETL/ELT design and orchestration

Master Data Management (MDM)

Databricks architecture and implementation

Key Responsibilities

Lead, define, and implement end-to-end modern data platforms on public cloud using Databricks

Design and manage scalable data models and storage solutions

Collaborate with enterprise architects, data architects, ETL developers & engineers, data scientists, and information designers to define required data structures, formats, pipelines, metadata, and workload orchestration capabilities

Establish data standards, governance policies, and best practices

Oversee the integration of new data technologies and tools

Lead the development of data pipelines, marts, and lakes

Ensure data solutions are compliant with security and regulatory standards

Address aspects such as data privacy & security, data ingestion & processing, data storage & compute, analytical & operational consumption, data modeling, data virtualization, self-service data preparation & analytics, AI enablement, and API integrations

Mentor data engineers and developers on best practices

Qualifications

Bachelor s or Master s degree in Computer Science, Engineering, or a related field

Relevant certifications in cloud platforms, data architecture, or governance

Technical Skills

Data Modelling: Conceptual, Logical, Physical modelling (ERwin, Power Designer, etc.)

Cloud: Azure (ADF, Synapse, Databricks), AWS (Redshift, Glue), GCP (Big Query)

Databases: SQL Server, Oracle, PostgreSQL, NoSQL (MongoDB, Cassandra)

Data Integration: Informatica, Talend, Apache NiFi

Big Data: Hadoop, Spark, Kafka

Governance Tools: Collibra, Alation, Azure Purview

Scripting: Python, SQL, Shell

DevOps/DataOps practices and CI/CD tools

Soft Skills

Strong leadership and stakeholder management

Excellent communication and documentation skills

Strategic thinking with problem-solving ability

Collaborative and adaptive in cross-functional teams

Experience in AI/ML data lifecycle support

Exposure to industry data standards and frameworks (TOGAF, DAMA-DMBOK)

Experience with real-time analytics and streaming data solutions

Work Experience Minimum 10 years in data engineering, architecture, or related roles

At least 5 years of hands-on experience in designing data platforms on Azure

Demonstrated knowledge of 2 full project cycles using Databricks as an architect

Experience supporting and working with cross-functional teams in a dynamic environment

Advanced working SQL knowledge and experience working with relational databases and unstructured datasets

Experience with stream-processing systems such as Storm, Spark-Streaming

Competitive salary and annual performance-based bonuses

Comprehensive health and optional Parental insurance.

Retirement savings plans and tax savings plans.

Work-Life Balance: Flexible work hours

Key Result Areas (KRAs)

Effective implementation of scalable and secure data architecture

Governance and compliance adherence

Standardization and optimization of data assets

Enablement of self-service analytics and data democratization

Key Performance Indicators (KPIs)

Architecture scalability and reusability metrics

Time-to-delivery for data initiatives

Data quality and integrity benchmarks

Satisfaction ratings from business stakeholders

Contact Informations: Click here to upload your CV / Resume We accept PDF, DOC, DOCX, JPG and PNG files SUBMIT APPLICATION

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