Data Architect - Datamatics Technologies - Career Page

Datamatics Global Services · Not specified · onsite · Posted 42d ago

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Datamatics Technologies

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Data Architect

Islamabad, Federal Teritory, Pakistan

Full Time

Senior Manager/Supervisor

Job Title: Data Architect

Experience: 9+ Years
Industry: Banking / Financial Services
Location:Pakistan
Employment Type: Full-Time

Job Summary

We are seeking an experienced Data Architect with a strong background in AI/ML and Big Data architectures to design, implement, and govern enterprise-wide data solutions. The ideal candidate will play a critical role in enabling data-driven decision-making, advanced analytics, and AI capabilities within a banking environment while ensuring compliance with regulatory and security standards.

Key Responsibilities

Design and implement enterprise data architecture across traditional systems, Big Data platforms, and cloud ecosystems.
Architect scalable data lakes, data warehouses, and lakehouse solutions supporting structured and unstructured data.
Define and manage data models, metadata frameworks, and data integration patterns for enterprise-wide use.
Build and optimize data pipelines for batch and real-time processing using technologies like Hadoop, Spark, and Kafka.
Enable AI/ML use cases by designing data platforms compatible with Python-based frameworks such as TensorFlow, PyTorch, and MLflow.
Lead cloud data architecture initiatives across AWS, Azure, and GCP, ensuring high availability, scalability, and cost efficiency.
Implement and enforce data governance, data quality, and data security frameworks using tools such as Collibra, Alation, and Apache Atlas.
Collaborate with cross-functional teams including data engineers, data scientists, business analysts, and IT teams.
Design and oversee ETL/ELT processes using tools like Informatica, Talend, and dbt.
Utilize orchestration frameworks such as Apache Airflow to automate and monitor workflows.
Ensure compliance with banking regulations, data privacy laws, and security standards.
Evaluate and recommend emerging technologies to enhance the organization's data capabilities.

Required Skills & Qualifications

Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, or related field.
9+ years of experience in data architecture, data engineering, or related roles, preferably in the banking or financial services industry.
Strong expertise in Big Data technologies: Hadoop, Spark, Kafka.
Hands-on experience with cloud platforms: AWS, Microsoft Azure, or Google Cloud Platform.
Proficiency in data modeling (conceptual, logical, physical) and database design.
Experience with data warehousing and lakehouse architectures (Snowflake, Databricks).
Strong understanding of AI/ML data pipelines and frameworks (Python, TensorFlow, PyTorch).
Expertise in ETL/ELT tools and data pipeline orchestration.
Knowledge of data governance, metadata management, and data quality frameworks.
Familiarity with banking data domains (risk, compliance, fraud, customer analytics).
Excellent problem-solving, communication, and stakeholder management skills.

Preferred Qualifications

Certifications in Cloud Platforms (AWS/Azure/GCP) or Data Architecture.
Experience with real-time streaming architectures.
Knowledge of regulatory frameworks such as Basel III, GDPR, or local banking compliance standards.
Exposure to Data Mesh or Data Fabric architectures.
Experience with API-based data integration and microservices architecture.

Key Competencies

Strategic Thinking
Data Governance & Compliance
Solution Architecture
Stakeholder Management
Innovation & Continuous Improvement

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Skills

InformaticaAimlApache SparkApache Kafkamlflowgoogle cloud platformamazon web servicesapache airflowdbtcollibraTalendApache HadoopPytorchTensorflowAlationApache AtlasDatabricksPythonSnowflakeMicrosoft Azurebig data architectures

About Datamatics Global Services

Datamatics Global Services

IT Services & Consulting

5.0k+

employees

1975

51 years old

Mumbai, Maharashtra

India

₹8.3L PA avg

Avg at Datamatics Global Services

About

Datamatics is an IT and BPM service company providing Intelligent Solutions for businesses to increase productivity and enhance customer experience

Industries

IT Services & ConsultingBPO/KPOFinancial Services

Employee ratings

10 reviews

3.3/ 5

Culture

2.5

Career growth

2.1

Work-life

2.7

Employees rate it well for

Work-Life Balance33Overall Company33

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Job Summary

Key Responsibilities

Design and implement enterprise data architecture across traditional systems, Big Data platforms, and cloud ecosystems.

Architect scalable data lakes, data warehouses, and lakehouse solutions supporting structured and unstructured data.

Define and manage data models, metadata frameworks, and data integration patterns for enterprise-wide use.

Build and optimize data pipelines for batch and real-time processing using technologies like Hadoop, Spark, and Kafka.

Enable AI/ML use cases by designing data platforms compatible with Python-based frameworks such as TensorFlow, PyTorch, and MLflow.

Lead cloud data architecture initiatives across AWS, Azure, and GCP, ensuring high availability, scalability, and cost efficiency.

Implement and enforce data governance, data quality, and data security frameworks using tools such as Collibra, Alation, and Apache Atlas.

Collaborate with cross-functional teams including data engineers, data scientists, business analysts, and IT teams.

Design and oversee ETL/ELT processes using tools like Informatica, Talend, and dbt.

Utilize orchestration frameworks such as Apache Airflow to automate and monitor workflows.

Ensure compliance with banking regulations, data privacy laws, and security standards.

Evaluate and recommend emerging technologies to enhance the organization's data capabilities.

Required Skills & Qualifications

Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, or related field.

9+ years of experience in data architecture, data engineering, or related roles, preferably in the banking or financial services industry.

Strong expertise in Big Data technologies: Hadoop, Spark, Kafka.

Hands-on experience with cloud platforms: AWS, Microsoft Azure, or Google Cloud Platform.

Proficiency in data modeling (conceptual, logical, physical) and database design.

Experience with data warehousing and lakehouse architectures (Snowflake, Databricks).

Strong understanding of AI/ML data pipelines and frameworks (Python, TensorFlow, PyTorch).

Expertise in ETL/ELT tools and data pipeline orchestration.

Knowledge of data governance, metadata management, and data quality frameworks.

Familiarity with banking data domains (risk, compliance, fraud, customer analytics).

Excellent problem-solving, communication, and stakeholder management skills.

Preferred Qualifications

Certifications in Cloud Platforms (AWS/Azure/GCP) or Data Architecture.

Experience with real-time streaming architectures.

Knowledge of regulatory frameworks such as Basel III, GDPR, or local banking compliance standards.

Exposure to Data Mesh or Data Fabric architectures.

Experience with API-based data integration and microservices architecture.