13 Data Architect jobs in Chennai

About the Role:

We are seeking a seasoned Data Engineering Architect with 15+ years of experience designing and scaling enterprise-grade data platforms to lead the architecture of our Connected Electric Vehicle (EV) Platform.

This role requires deep expertise in cloud-native (AWS & GCP) data ecosystems, real-time streaming infrastructure, and architecting solutions for high-velocity, high-volume telemetry generated by Electric Vehicle.

Skill Sets Required:

• 15+ years of experience in Data Architecture and Engineering
• Deep understanding of structured and unstructured data ecosystems
• Hands-on experience with ETL, ELT, stream processing, querying, and data modeling
• Proficiency in tools and languages such as Java, Spark, Kafka, Airflow, and Python
• Proficiency in SQL and MongoDB
• Proven experience in building and maintaining data warehouses and data lakes
• Experience in implementing data quality standards and performing exploratory data analysis (EDA)
• Experience with any public cloud platform: GCP, AWS, or Azure
• Strong knowledge of data governance, privacy, and compliance standards
• Expertise in designing high-performance and cost-optimized data engineering pipelines leveraging Medallion Architecture
• A strategic mindset with the ability to execute hands-on when needed

Good to Have:

• Knowledge of GraphQL/Graph databases
• Exposure to connected vehicle platforms
• Experience in the EV or automotive domain
• Knowledge of API development
• Exposure to data mesh and data fabric concepts

Responsibilities:

• Design scalable, secure, and high-performance data architectures across cloud and on-premise environments for our connected vehicle platform
• Lead the end-to-end architecture of data pipelines and real-time streaming solutions using Kafka, Kinesis, Google Pub/Sub, Apache Flink, or Dataflow.
• Establish best practices for tiered storage across hot, warm, and cold data using BigQuery, Redshift, S3/GCS, and Delta Lake.
• Collaborate with cross-functional teams and business stakeholders to ensure data solutions meet analytical and operational requirements
• Enable AI/ML readiness through clean, governed, and performant data pipelines for predictive models.
• Evaluate and recommend tools and technologies to improve the data platform by conducting proof of concepts (PoCs)
• Ensure compliance with data security, privacy, and regulatory standards
• Mentor and guide data engineers and solution architects
• Establish best practices and coding standards for data engineering teams
• Stay current with emerging technologies and drive adoption of modern data practices
• Lead and contribute to technical discussions and decision-making

Qualifications:

• Bachelor’s or Master’s degree in any discipline
• 15+ years of industry experience, with a minimum of 10 years in data engineering

Hands-On | Micro Data Lakes | Enterprise Data Strategy

Are you a hands-on Data Architect who thrives on solving complex data problems across structured and unstructured sources? Do you enjoy designing micro data lakes and driving enterprise-wide data strategy? If so, we want to hear from you.

What You Will Do

Design and build micro data lakes tailored to lending domain

Define and implement enterprise data strategies including modelling, lineage, and governance

Architect and build robust data pipelines for batch and real-time data ingestion

Develop strategies for extracting, transforming, and storing data from APIs, PDFs, logs, databases, and more

Establish best practices for data quality, metadata management, and data lifecycle control

Hands-on in implementation of processes, strategies and tools to create differentiated products. – MUST HAVE

Collaborate with engineering and product teams to align data architecture with business goals

Evaluate and integrate modern data platforms and tools such as Databricks, Spark, Kafka, Snowflake, AWS, GCP, Azure

Mentor data engineers and advocate for engineering excellence in data practices

What You Bring

10+ years of experience in data architecture and engineering

Deep understanding of structured and unstructured data ecosystems

Hands-on experience with ETL, ELT, stream processing, querying and data modelling

Proficiency in tools and languages such as Spark, Kafka, Airflow, SQL, Amundsen, Glue Catalog and Python

Expertise in cloud-native data platforms including AWS, Azure, or GCP

Strong grounding in data governance, privacy, and compliance standards

A strategic mindset with the ability to execute hands-on when needed

Nice to Have

Exposure to the lending domain

Exposure to ML pipelines or AI integrations

Background in fintech, lending, or regulatory data environments

What We Offer

An opportunity to lead data-first transformation, create products that accelerate AI adoption

Autonomy to design, build, and scale modern data architecture

A forward-thinking, collaborative, and tech-driven culture

Access to the latest tools and technologies in the data ecosystem

Location: Chennai

Experience: 10-15 Years | Full-Time | Work From Office

Key Responsibilities

• Design and Implement Data Architectures: Architect and build scalable, end-to-end data solutions on GCP, encompassing data ingestion, transformation, storage, and consumption.
• Develop Data Pipelines: Design and develop ETL/ELT data pipelines using tools like Apache Airflow (Cloud Composer) and programming languages such as Python and SQL for batch and real-time processing.
• Create Data Models: Build logical and physical data models, including dimensional modelling and schema design, to support data warehousing, data lakes, and analytics.
• Ensure Data Quality and Governance: Establish and enforce data governance, security, and quality standards, implementing data validation and testing procedures.
• Collaborate with Stakeholders: Work with data engineers, business analysts, data scientists, and product owners to translate business requirements into technical data solutions.
• Optimize GCP Services: Optimize the performance and cost-effectiveness of GCP services, particularly Big Query, for analytics and data storage.
• Provide Technical Guidance: Lead architectural reviews, provide technical guidance on cloud-native data strategies, and mentor engineering teams on GCP best practices.

Required Skills and Knowledge

• Google Cloud Platform (GCP): Expertise with GCP services like BigQuery, Cloud Storage, Cloud SQL, and Cloud Composer.
• Data Modelling: Proficiency in designing data models for data warehouses and data lakes.
• ETL/ELT: Experience with designing and building data pipelines using tools like Apache Airflow.
• Programming: Strong skills in SQL and Python for data processing and development.
• Data Governance: Understanding and ability to implement data governance, metadata management, and security policies.
• Collaboration: Strong communication skills to work with cross-functional teams and explain complex technical concepts.

Job title

Azure Data Architect

Experience: 10+ Years

Overview of Role / Role Purpose

As an Azure Data Architect you will be a key member of the Global GTS M&A team. This role will be proficient in investigating, decomposing, and combining data of different data sources and types. Ideal candidates are prepared to design appropriate solutions to support merger data needs. The Azure Data Architect will partner with other team members on the creation of best-practices approach to capture data from disparate applications into an Azure Data Lake for cleaning, curation and mapping into various application destinations meeting Gallagher approved standards. They will identify and explore new data sources and be primarily focused on developing integration processes between systems and create thorough diagrams and documentation. They will also be responsible for identifying datasets targeted for on-prem migration and architecting the requisite platform for hosting that data from within the Gallagher datacenter.

Core Responsibilities

• Identifies, designs, and implements internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Investigates data, data sources, and performs data quality analysis.
• Collaborates with other Architects and Data Engineers to help adopt best-practices in data system creation, data integrity, test design, analysis, validation, and documentation.
• Creates and maintains optimal data pipeline architecture for extraction, transformation, and loading of data from various data sources – both internal and external.
• Assembles large, complex sets of data that meet non-functional and functional business requirements.
• Builds industrialized analytic datasets and delivery mechanisms that utilize the data pipeline to deliver actionable insights.
• Communicates and maintains master data, metadata, data management repositories, logical data models, data standards.
• Works with stakeholders including the executive, product, data and technology teams to support their data infrastructure needs while assisting with data-related technical issues.

Key Skills and Experience

• Excellent analysis and problem-solving skills
• Effective time-management skills
• Ability to adapt to ever-changing system environments and understand all business applications
• Desire to learn new technologies and adapt requirements for future cloud solutions
• Good organizational skills and a strict attention to detail and proven ability to follow through
• Strong interpersonal skills
• Ability to develop effective working relationships with stakeholders
• Hands-on experienced with designing, moving and transforming data to/from Microsoft SQL Server, Azure SQL, Azure SQL DW, Dynamics CRM, Dynamics 365.
• Hands-on experience integration technologies such as SQL Server Integration Services, Azure Data Factory, Azure Logic Apps, Power Automate Azure Integration Services or similar technologies.
• Mastery of relational SQL and NoSQL databases
• Mastery knowledge of Snowlflake in both AWS and Azure clouds
• Experienced with data wrangling and preparation for use within PowerBI
• Strong written and verbal communication skills including the ability to effectively collaborate with multi-disciplinary groups and all organizational levels.

Education / Qualifications

• Bachelor's degree in Computer Science, Information Technology, or a related field and minimum 3 years of prior relevant experience.

Notice period: 30 days max

We are a leading international Bank that is going through a significant transformation of its front-to-back operations, marked as one of the banks top 3 transformation agendas.

F2B Business Architecture is a small central global team in CIB- CTB to support the delivery of this key front-to-back (F2B) transformation priorities of the management board. The Data Architecture team will play the central role of defining the data model that will align the business processes and ensure data lineage, effective controls, and implement efficient client strategy and reporting solutions. This will require building strong relationships with key stakeholders and help deliver tangible value.

The role will report to the India Head of Investment Bank and Cross Product F2B Operations.

Responsibilities:

- Be part of the CTB team to define and manage Data models used to implement solutions to automate F2B business processes and controls

- Ensure the models follow the bank's data modelling standards and principles and influence them as necessary

- Actively partner with various functional leads & teams to socialize the data models towards adoption and execution of front-to-back solutions

Mandatory Skills Description:

- 10+ years in financial services, preferably Strategy and solutions in the Corporate and Investment Banking domain.

- Strong Data analysis skills, SQL/Python experience, and the ability to build data models are desirable.

- Must have implemented data models.

- Worked on architectural design by coordinating with both business and technology teams.

- Excellent working knowledge of the functional side and business data.

- Strong Knowledge of transaction banking domain process and controls for banking & trading business to drive conversation with business SMEs. Experience in developing models for transacting banking products is preferable.

- Experience working in an enterprise agile environment in a matrix organization.

- Critical problem-solving skills, able to think tactically and strategically.

Nice-to-Have Skills Description:

Good Tech stack

Languages:

English: C2 Proficient

As a Senior Data Architect in the BFSI domain, you will be responsible for designing and governing data architecture across core banking, Wealth Management and financial platforms. Youll lead initiatives that span legacy systems (mainframes) to modern cloud-native and NoSQL solutions, ensuring regulatory compliance, data lineage, and high availability for mission-critical applications.

Key Responsibilities:

• Architect scalable data solutions for core banking , Wealth Management , risk management , fraud detection , and regulatory reporting .
• Design data models  for transactional systems, data warehouses, and real-time analytics platforms.
• Lead data migration  from legacy systems (e.g., DB2, VSAM) to cloud platforms like Snowflake , Azure Synapse , or Google BigQuery . Lead Data migration from Oracle to Postgres , SQL Server to Postgres 
• Collaborate with compliance teams to ensure data governance , auditability , and regulatory alignment  (e.g., Basel III, IFRS, GDPR).
• Build and optimize ETL/ELT pipelines  for high-volume financial data using tools like Informatica , Talend , Apache NiFi , or Azure Data Factory .
• Integrate data across core banking systems , Wealth Management Systems , CRM , insurance platforms , and digital channels .
• Define metadata standards, lineage tracking, and master data management frameworks.
• Mentor data engineers and analysts; contribute to architectural reviews and BFSI-specific best practices.

Domain Expertise:

• Deep understanding of BFSI data domains : customer, account, transaction, trading, portfolios, positions, credit, risk, claims, policy, and underwriting.
• Experience with financial data modeling , including ledger structures , risk hierarchies , and regulatory taxonomies .

Data Modeling & Architecture:

• Proficiency in Erwin , PowerDesigner , or Toad Data Modeler .
• Experience with 3NF , dimensional modeling , data vault , and canonical models .

Key Responsibilities:

• Architect scalable data solutions for core banking/wealth management , risk management , fraud detection , and regulatory reporting .
• Design data models  for transactional systems, data warehouses, and real-time analytics platforms.
• Lead data migration  from legacy systems (e.g., DB2, VSAM) to cloud platforms like Snowflake , Azure Synapse , or Google BigQuery. Lead Data Migration between multiple databases like Oracle to Postgres.
• Collaborate with compliance teams to ensure data governance , auditability , and regulatory alignment  (e.g., Basel III, IFRS, GDPR).
• Build and optimize ETL/ELT pipelines  for high-volume financial data using tools like Informatica , Talend , Apache NiFi , or Azure Data Factory .
• Integrate data across core banking systems , CRM , insurance platforms , and digital channels .
• Define metadata standards, lineage tracking, and master data management frameworks.
• Mentor data engineers and analysts; contribute to architectural reviews and BFSI-specific best practices.

Preferred Qualifications:

• Bachelors/Masters in Computer Science, Information Systems, or Finance
• Certifications: GCP Certification, AWS Data Analytics, Azure Data Engineer, CDMP (DAMA), TOGAF
• Experience with financial regulations  and reporting standards  (e.g., BCBS 239, FATCA)

As an Application Lead , you will be responsible for leading the design, development, and configuration of data-driven applications, with a focus on Snowflake Data Warehouse. Acting as the primary point of contact, you will collaborate with cross-functional teams to ensure application requirements are met while maintaining alignment with business goals. You will guide your team throughout the development lifecycle, resolve technical challenges, and ensure delivery excellence in both performance and quality.

Act as the Subject Matter Expert (SME) for Snowflake Data Warehouse solutions.

Lead and manage a development team, ensuring high performance and collaboration.

Take responsibility for team-level decisions and accountability for deliverables.

Collaborate with multiple teams across the organization to drive key architectural and strategic decisions.

Provide innovative and scalable solutions to data-related challenges, both within the immediate team and across projects.

Facilitate knowledge sharing , promote adoption of best practices, and support ongoing team development.

Monitor project milestones , ensure timely delivery of application components, and maintain a focus on quality and efficiency.

Drive improvements in data warehousing processes and contribute to continuous optimization.

Strong proficiency in Snowflake Data Warehouse with at least 5 years of hands-on experience.

Deep understanding of cloud-based data solutions and scalable architecture.

Experience with ETL processes and data integration tools (e.g., Informatica, Talend, Matillion).

Proficiency in SQL and data modeling techniques (e.g., dimensional, star-schema).

Knowledge of performance tuning and optimization for data warehouse solutions.