data analyst

data engineer

business analyst

data scientist

ai architect

data architect

Datamatics Global Services Ltd

<div><h2 class="jobSectionHeader">Job Title: Data Architect</h2>
Experience: 9+ Years 
Industry: Banking / Financial Services 
Location:Pakistan 
Employment Type: Full-Time<h2 class="jobSectionHeader">
Job Summary</h2>
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.<h2 class="jobSectionHeader">
Key Responsibilities</h2><ul><li>
Design and implement enterprise data architecture across traditional systems, Big Data platforms, and cloud ecosystems.</li><li>
Architect scalable data lakes, data warehouses, and lakehouse solutions supporting structured and unstructured data.</li><li>
Define and manage data models, metadata frameworks, and data integration patterns for enterprise-wide use.</li><li>
Build and optimize data pipelines for batch and real-time processing using technologies like Hadoop, Spark, and Kafka.</li><li>
Enable AI/ML use cases by designing data platforms compatible with Python-based frameworks such as TensorFlow, PyTorch, and MLflow.</li><li>
Lead cloud data architecture initiatives across AWS, Azure, and GCP, ensuring high availability, scalability, and cost efficiency.</li><li>
Implement and enforce data governance, data quality, and data security frameworks using tools such as Collibra, Alation, and Apache Atlas.</li><li>
Collaborate with cross-functional teams including data engineers, data scientists, business analysts, and IT teams.</li><li>
Design and oversee ETL/ELT processes using tools like Informatica, Talend, and dbt.</li><li>
Utilize orchestration frameworks such as Apache Airflow to automate and monitor workflows.</li><li>
Ensure compliance with banking regulations, data privacy laws, and security standards.</li><li>
Evaluate and recommend emerging technologies to enhance the organization&rsquo;s data capabilities.</li></ul><h2 class="jobSectionHeader">
Required Skills &amp; Qualifications</h2><ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Information Systems, Data Science, or related field.</li><li>
9+ years of experience in data architecture, data engineering, or related roles, preferably in the banking or financial services industry.</li><li>
Strong expertise in Big Data technologies: Hadoop, Spark, Kafka.</li><li>
Hands-on experience with cloud platforms: AWS, Microsoft Azure, or Google Cloud Platform.</li><li>
Proficiency in data modeling (conceptual, logical, physical) and database design.</li><li>
Experience with data warehousing and lakehouse architectures (Snowflake, Databricks).</li><li>
Strong understanding of AI/ML data pipelines and frameworks (Python, TensorFlow, PyTorch).</li><li>
Expertise in ETL/ELT tools and data pipeline orchestration.</li><li>
Knowledge of data governance, metadata management, and data quality frameworks.</li><li>
Familiarity with banking data domains (risk, compliance, fraud, customer analytics).</li><li>
Excellent problem-solving, communication, and stakeholder management skills.</li></ul><h2 class="jobSectionHeader">
Preferred Qualifications</h2><ul><li>
Certifications in Cloud Platforms (AWS/Azure/GCP) or Data Architecture.</li><li>
Experience with real-time streaming architectures.</li><li>
Knowledge of regulatory frameworks such as Basel III, GDPR, or local banking compliance standards.</li><li>
Exposure to Data Mesh or Data Fabric architectures.</li><li>
Experience with API-based data integration and microservices architecture.</li></ul><h2 class="jobSectionHeader">
Key Competencies</h2><ul><li>
Strategic Thinking</li><li>
Data Governance &amp; Compliance</li><li>
Solution Architecture</li><li>
Stakeholder Management</li><li>
Innovation &amp; Continuous Improvement</li></ul>
CQRSVKAboh</div>

Data Architect

Datamatics Technologies

<div>
 
 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
 
 <ul>
 <li>
 Design and implement
 
 enterprise data architecture
 
 across traditional systems, Big Data platforms, and cloud ecosystems
 </li>
 <li>
 Architect scalable
 
 data lakes, data warehouses, and lakehouse solutions
 
 supporting structured and unstructured data
 </li>
 <li>
 Define and manage
 
 data models, metadata frameworks, and data integration patterns
 
 for enterprise-wide use
 </li>
 <li>
 Build and optimize
 
 data pipelines
 
 for batch and real-time processing using technologies like Hadoop, Spark, and Kafka
 </li>
 <li>
 Enable
 
 AI/ML use cases
 
 by designing data platforms compatible with Python-based frameworks such as TensorFlow, PyTorch, and MLflow
 </li>
 <li>
 Lead cloud data architecture initiatives across
 
 AWS, Azure, and GCP
 
 , ensuring high availability, scalability, and cost efficiency
 </li>
 <li>
 Implement and enforce
 
 data governance, data quality, and data security frameworks
 
 using tools such as Collibra, Alation, and Apache Atlas
 </li>
 <li>
 Collaborate with cross-functional teams including
 
 data engineers, data scientists, business analysts, and IT teams
 
 </li>
 <li>
 Design and oversee
 
 ETL/ELT processes
 
 using tools like Informatica, Talend, and dbt
 </li>
 <li>
 Utilize orchestration frameworks such as
 
 Apache Airflow
 
 to automate and monitor workflows
 </li>
 <li>
 Ensure compliance with
 
 banking regulations, data privacy laws, and security standards
 
 </li>
 <li>
 Evaluate and recommend emerging technologies to enhance the organization&rsquo;s data capabilities
 </li>
 </ul>
 
 Required Skills &amp; Qualifications
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in
 
 Computer Science, Information Systems, Data Science, or related field
 
 </li>
 <li>
 9+ years of experience in
 
 data architecture, data engineering, or related roles
 
 , preferably in the banking or financial services industry
 </li>
 <li>
 Strong expertise in
 
 Big Data technologies
 
 : Hadoop, Spark, Kafka
 </li>
 <li>
 Hands-on experience with
 
 cloud platforms
 
 : AWS, Microsoft Azure, or Google Cloud Platform
 </li>
 <li>
 Proficiency in
 
 data modeling (conceptual, logical, physical)
 
 and database design
 </li>
 <li>
 Experience with
 
 data warehousing and lakehouse architectures
 
 (Snowflake, Databricks)
 </li>
 <li>
 Strong understanding of
 
 AI/ML data pipelines and frameworks
 
 (Python, TensorFlow, PyTorch)
 </li>
 <li>
 Expertise in
 
 ETL/ELT tools
 
 and data pipeline orchestration
 </li>
 <li>
 Knowledge of
 
 data governance, metadata management, and data quality frameworks
 
 </li>
 <li>
 Familiarity with
 
 banking data domains
 
 (risk, compliance, fraud, customer analytics)
 </li>
 <li>
 Excellent problem-solving, communication, and stakeholder management skills
 </li>
 </ul>
 
 Preferred Qualifications
 
 <ul>
 <li>
 Certifications in
 
 Cloud Platforms (AWS/Azure/GCP)
 
 or
 
 Data Architecture
 
 </li>
 <li>
 Experience with
 
 real-time streaming architectures
 
 </li>
 <li>
 Knowledge of
 
 regulatory frameworks
 
 such as Basel III, GDPR, or local banking compliance standards
 </li>
 <li>
 Exposure to
 
 Data Mesh or Data Fabric architectures
 
 </li>
 <li>
 Experience with
 
 API-based data integration and microservices architecture
 
 </li>
 </ul>
 
 Key Competencies
 
 <ul>
 <li>
 Strategic Thinking
 </li>
 <li>
 Data Governance &amp; Compliance
 </li>
 <li>
 Solution Architecture
 </li>
 <li>
 Stakeholder Management
 </li>
 <li>
 Innovation &amp; Continuous Improvement
 </li>
 </ul>
</div>

CodeNinja

<div>About CodeNinja
CodeNinja is a full-stack AI delivery company that helps enterprises, governments, and software acquirers build and operate intelligence-driven systems for mission-critical workflows. We specialize in deploying AI into real operations&mdash;combining strong engineering fundamentals with AI-native delivery to create measurable value, resilience, and long-term ownership for our clients. Our global footprint and delivery model are supported by AI Labs, AI Pods, and Global Capability Centers, enabling teams to co-engineer scalable platforms across regions and time zones.
Role Purpose
Lead the ERP program&rsquo;s data strategy by ensuring data readiness, conceptual data modelling, reporting data sourcing, and structured data migration planning, enabling a reliable, unified data foundation across all modules.
Key Responsibilities<ul><li>Conduct comprehensive assessment of legacy data sources:</li></ul>
o Inventory, Maintenance (MRO), Procurement, HR, Technical Docs<ul><li>Identify:</li></ul>
o Data quality issues (duplicates, missing, inconsistencies)
o Data ownership and governance gaps
o Redundant/siloed datasets<ul><li>Define data cleansing and standardization approach</li><li>Produce Data Readiness Assessment Report</li><li>Define end-to-end Data Migration Strategy, including:</li></ul>
o Migration approach (phased, module-wise, or big-bang)
o Data prioritization (master data vs transactional vs historical)<ul><li>Develop Data Mapping Specifications:</li></ul>
o Legacy ERP field-level mappings
o Transformation rules and standardization logic
o Handling of missing/invalid data<ul><li>Define Data Cleansing &amp; Preparation Plan:</li></ul>
o Deduplication rules
o Data enrichment where required
o Validation checkpoints before migration<ul><li>Design Migration Execution Plan:</li></ul>
o Migration cycles (mock runs, dry runs, final cutover)
o Rollback strategy in case of failure
o Downtime and cutover planning<ul><li>Define Data Validation &amp; Reconciliation Framework:</li></ul>
o Pre-migration vs post-migration validation rules
o Reconciliation reports (counts, totals, relationships)
o Sign-off criteria for each module<ul><li>Produce key deliverables:</li></ul>
o Data Migration Plan
o Data Mapping Documents
o Data Validation &amp; Reconciliation Reports<ul><li>Identify and enable AI/ML use cases, such as:</li></ul>
o Predictive maintenance modeling
o Inventory demand forecasting
o Supplier performance analytics<ul><li>Leverage AI tools for:</li></ul>
o Data profiling and anomaly detection
o Data quality assessment and cleansing recommendations
o Advanced analytics and insights generation<ul><li>Define enterprise conceptual data model:</li></ul>
o Assets, Inventory, Work Orders, Suppliers, Workforce, Technical Docs<ul><li>Establish:</li></ul>
o Entity relationships
o Master data definitions
o Data standardization rules<ul><li>Support BI teams for dashboards and analytics</li><li>Align data models with business workflows</li><li>Ensure requirements are data-feasible and consistent</li></ul> 
Requirements 
3. Required Skills &amp; Experience
Mandatory<ul><li> 5 - 8 years in Data Analyst / Data Architecture roles</li><li>Experience in large-scale ERP or enterprise data transformation programs</li><li>Strong expertise in:</li></ul>
o Data modelling (conceptual &amp; logical)
o Data migration and cleansing
o Data warehousing and reporting
Technical Expertise<ul><li>Strong knowledge of:</li></ul>
o ETL processes and migration tools
o SQL and relational databases
o API-based integrations<ul><li>Experience with BI tools (Power BI, Tableau)</li></ul>
Preferred<ul><li>Experience in ERP &amp; Enterprise Data Management (logistics, manufacturing)</li><li>Exposure to:</li></ul>
o Maintenance (MRO) data
o Inventory systems
o Technical documentation repositories<ul><li>Demonstrated experience using AI/ML tools or platforms, such as:</li></ul>
o Data analysis and prediction tools
o AI-assisted data modeling or profiling tools<ul><li>Ability to translate data into AI-driven insights for decision-making</li></ul>
Why Join CodeNinja?<ul><li>
Work on impactful ERP transformation projects at enterprise scale
</li><li>Shape end-to-end data strategy, migration, and architecture
</li><li>Leverage AI/ML for advanced data insights and analytics
</li><li>Collaborate with cross-functional teams and drive business decisions
</li><li>Build scalable data models and governance frameworks
</li><li>Grow in a culture of innovation, ownership, and continuous learning</li></ul>
Equal Opportunity Statement
We are an equal opportunity employer and are committed to fostering an inclusive, diverse, and equitable workplace. We do not discriminate based on race, religion, gender, age, disability, nationality, marital status, or any other protected characteristic under applicable law. We encourage candidates from all backgrounds to apply. 
Benefits 
<ul><li>
Provident Fund</li><li>
Gym Membership
</li><li>Leaves as per the company policy
</li><li>Company-paid trips
</li><li>Easy Loan Facility for Employees
</li><li>Yearly increment
</li><li>Maternity Benefits (Leaves &amp; WFH)
</li><li>Health Insurance (Maternity covered) &ndash; includes spouse and parents (till age 80)</li></ul></div>

Data Engineer/Data Architect

CodeNinja Inc.

<div>
 
 About CodeNinja
 
 
 
 
 CodeNinja
 
 is a full-stack AI delivery company that helps enterprises, governments, and software acquirers build and operate intelligence-driven systems for mission-critical workflows. We specialize in deploying AI into real operations&mdash;combining strong engineering fundamentals with AI-native delivery to create measurable value, resilience, and long-term ownership for our clients. Our global footprint and delivery model are supported by AI Labs, AI Pods, and Global Capability Centers, enabling teams to co-engineer scalable platforms across regions and time zones.
 
 
 
 
 Role Purpose
 
 
 
 
 Lead the ERP program's data strategy by ensuring data readiness, conceptual data modelling, reporting data sourcing, and structured data migration planning, enabling a reliable, unified data foundation across all modules.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Conduct comprehensive assessment of legacy data sources:
 </li>
 <li>
 Inventory, Maintenance (MRO), Procurement, HR, Technical Docs
 </li>
 <li>
 Identify:
 </li>
 <li>
 Data quality issues (duplicates, missing, inconsistencies)
 </li>
 <li>
 Data ownership and governance gaps
 </li>
 <li>
 Redundant/siloed datasets
 </li>
 <li>
 Define data cleansing and standardization approach
 </li>
 <li>
 Produce Data Readiness Assessment Report
 </li>
 <li>
 Define end-to-end Data Migration Strategy, including:
 </li>
 <li>
 Migration approach (phased, module-wise, or big-bang)
 </li>
 <li>
 Data prioritization (master data vs transactional vs historical)
 </li>
 <li>
 Develop Data Mapping Specifications:
 </li>
 <li>
 Legacy &rarr; ERP field-level mappings
 </li>
 <li>
 Transformation rules and standardization logic
 </li>
 <li>
 Handling of missing/invalid data
 </li>
 <li>
 Define Data Cleansing &amp; Preparation Plan:
 </li>
 <li>
 Deduplication rules
 </li>
 <li>
 Data enrichment where required
 </li>
 <li>
 Validation checkpoints before migration
 </li>
 <li>
 Design Migration Execution Plan:
 </li>
 <li>
 Migration cycles (mock runs, dry runs, final cutover)
 </li>
 <li>
 Rollback strategy in case of failure
 </li>
 <li>
 Downtime and cutover planning
 </li>
 <li>
 Define Data Validation &amp; Reconciliation Framework:
 </li>
 <li>
 Pre-migration vs post-migration validation rules
 </li>
 <li>
 Reconciliation reports (counts, totals, relationships)
 </li>
 <li>
 Sign-off criteria for each module
 </li>
 <li>
 Produce key deliverables:
 </li>
 <li>
 Data Migration Plan
 </li>
 <li>
 Data Mapping Documents
 </li>
 <li>
 Data Validation &amp; Reconciliation Reports
 </li>
 <li>
 Identify and enable AI/ML use cases, such as:
 </li>
 <li>
 Predictive maintenance modeling
 </li>
 <li>
 Inventory demand forecasting
 </li>
 <li>
 Supplier performance analytics
 </li>
 <li>
 Leverage AI tools for:
 </li>
 <li>
 Data profiling and anomaly detection
 </li>
 <li>
 Data quality assessment and cleansing recommendations
 </li>
 <li>
 Advanced analytics and insights generation
 </li>
 <li>
 Define enterprise conceptual data model:
 </li>
 <li>
 Assets, Inventory, Work Orders, Suppliers, Workforce, Technical Docs
 </li>
 <li>
 Establish:
 </li>
 <li>
 Entity relationships
 </li>
 <li>
 Master data definitions
 </li>
 <li>
 Data standardization rules
 </li>
 <li>
 Support BI teams for dashboards and analytics
 </li>
 <li>
 Align data models with business workflows
 </li>
 <li>
 Ensure requirements are data-feasible and consistent
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Required Skills &amp; Experience
 
 
 </li>
 </ul>
 
 Mandatory
 
 
 
 <ul>
 <li>
 5 - 8 years in Data Analyst / Data Architecture roles
 </li>
 <li>
 Experience in large-scale ERP or enterprise data transformation programs
 </li>
 <li>
 Strong expertise in:
 </li>
 <li>
 Data modelling (conceptual &amp; logical)
 </li>
 <li>
 Data migration and cleansing
 </li>
 <li>
 Data warehousing and reporting
 
 
 </li>
 </ul>
 
 Technical Expertise
 
 
 
 <ul>
 <li>
 Strong knowledge of:
 </li>
 <li>
 ETL processes and migration tools
 </li>
 <li>
 SQL and relational databases
 </li>
 <li>
 API-based integrations
 </li>
 <li>
 Experience with BI tools (Power BI, Tableau)
 
 
 </li>
 </ul>
 
 Preferred
 
 
 
 <ul>
 <li>
 Experience in ERP &amp; Enterprise Data Management (logistics, manufacturing)
 </li>
 <li>
 Exposure to:
 </li>
 <li>
 Maintenance (MRO) data
 </li>
 <li>
 Inventory systems
 </li>
 <li>
 Technical documentation repositories
 </li>
 <li>
 Demonstrated experience using AI/ML tools or platforms, such as:
 </li>
 <li>
 Data analysis and prediction tools
 </li>
 <li>
 AI-assisted data modeling or profiling tools
 </li>
 <li>
 Ability to translate data into AI-driven insights for decision-making
 
 
 </li>
 </ul>
 
 Why Join CodeNinja?
 
 
 
 <ul>
 <li>
 Work on impactful ERP transformation projects at enterprise scale
 </li>
 <li>
 Shape end-to-end data strategy, migration, and architecture
 </li>
 <li>
 Leverage AI/ML for advanced data insights and analytics
 </li>
 <li>
 Collaborate with cross-functional teams and drive business decisions
 </li>
 <li>
 Build scalable data models and governance frameworks
 </li>
 <li>
 Grow in a culture of innovation, ownership, and continuous learning
 
 
 </li>
 </ul>
 
 Equal Opportunity Statement
 
 
 
 We are an equal opportunity employer and are committed to fostering an inclusive, diverse, and equitable workplace. We do not discriminate based on race, religion, gender, age, disability, nationality, marital status, or any other protected characteristic under applicable law. We encourage candidates from all backgrounds to apply.
 
 
 
 Benefits
 
 
 
 <ul>
 <li>
 Provident Fund
 </li>
 <li>
 Gym Membership
 </li>
 <li>
 Leaves as per the company policy
 </li>
 <li>
 Company-paid trips
 </li>
 <li>
 Easy Loan Facility for Employees
 </li>
 <li>
 Yearly increment
 </li>
 <li>
 Maternity Benefits (Leaves &amp; WFH)
 </li>
 <li>
 Health Insurance (Maternity covered) - includes spouse and parents (till age 80)
 </li>
 </ul>
</div>

Data Analyst/Data Architect

Arpatech

Role &amp; Responsibilities:<ul><li>Design and implement scalable ETL/ELT pipelines for data ingestion, transformation, and storage.</li><li>Optimize data workflows to improve performance and maintain high scalability.</li><li>Integrate data from multiple sources into centralized data platforms.</li><li>Architect and maintain databases, data lakes, and data warehouses for both structured and unstructured datasets.</li><li>Monitor and validate data to ensure accuracy, consistency, and completeness.</li><li>Implement data security, governance, and compliance controls aligned with industry standards.</li><li>Collaborate with data analysts, AI engineers, and cross-functional teams to gather and define data requirements.</li><li>Provide technical support for analytics, BI, and reporting platforms.</li><li>Evaluate new tools and technologies to enhance data architecture and performance.</li><li>Maintain detailed documentation and update technical guides regularly.</li></ul>Requirements:<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Science, or a related discipline.</li><li>3&ndash;4 years of hands-on experience in building and managing data pipelines and data architectures.</li><li>Demonstrated experience designing and managing data pipelines and data architectures.</li><li>Strong knowledge of SQL and NoSQL databases, data modeling concepts, and schema design.</li><li>Hands-on expertise with data processing frameworks such as Apache Spark or Hadoop.</li><li>Experience working with major cloud platforms (AWS, Azure, or Google Cloud).</li><li>Proficiency in programming languages such as Python, Scala, or Java.</li></ul>Preferred Skills:<ul><li>Experience with data visualization tools (e.g., Power BI, Tableau).</li><li>Knowledge of streaming and real-time data technologies (e.g., Kafka, Flink).</li><li>Professional certifications in cloud data services (e.g., AWS Certified Data Analytics, Azure Data Engineer).</li></ul>Shift timings: 9 AM - 6 PM Karachi &amp; Islamabad (Onsite) &amp; Remote for other cities.Work Location: Remote

Data Engineer

Taraki

<div>
 Our client
 
 Big Entities
 
 is looking for
 
 AI Architect
 
 in
 
 Lahore.
 
 
 
 
 Job Description:
 
 
 
 We are seeking a Senior AI Engineer to lead the technical delivery of an intelligent document processing platform. This role combines technical leadership with hands-on engineering. You will define the AI processing strategy, guide the engineering team, and be accountable for the quality and scalability of the platform across a large corpus of enterprise documents.
 
 
 
 Key Responsibilities :
 
 
 
 <ul>
 <li>
 Own the end-to-end AI architecture across ingestion, classification, extraction, indexing, and retrieval.
 </li>
 <li>
 Define the hybrid AI strategy &mdash; determining when to use deep learning models, traditional NLP, and LLMs.
 </li>
 <li>
 Make architectural decisions on model routing, chunking strategies, and cost-quality trade-offs at scale.
 </li>
 <li>
 Define the information extraction framework, confidence scoring model, and output structure.
 </li>
 <li>
 Lead the vector indexing and RAG retrieval layer, including embedding models and semantic search tuning.
 </li>
 <li>
 Guide and mentor AI Engineers &mdash; reviewing code, setting standards, and providing technical direction.
 </li>
 <li>
 Collaborate with the Full-Stack Developer on API contracts and pipeline output integration.
 </li>
 <li>
 Drive performance optimisation, error handling, and fallback mechanisms across the pipeline.
 </li>
 <li>
 Produce technical documentation and handover materials.
 </li>
 <li>
 Serve as the primary technical point of contact with client stakeholders.
 
 
 
 </li>
 </ul>
 
 Required Skills:
 
 
 
 <ul>
 <li>
 6+ years of experience in AI/ML engineering, with at least 1 year in a senior or architect-level role.
 </li>
 <li>
 Deep expertise in Python 3 and the modern AI/NLP stack.
 </li>
 <li>
 Proven experience deploying production AI pipelines on Azure.
 </li>
 <li>
 Strong understanding of LLM orchestration, prompt engineering, RAG architecture, and embedding strategies.
 </li>
 <li>
 Experience with hybrid AI approaches combining deep learning, traditional NLP, and LLMs.
 </li>
 <li>
 Experience processing large corpora of heterogeneous documents at scale.
 </li>
 <li>
 Experience navigating enterprise cloud environments with security and compliance constraints.
 </li>
 <li>
 Track record of mentoring engineers and maintaining engineering standards.
 
 
 
 </li>
 </ul>
 
 Preferred Qualifications:
 
 
 
 <ul>
 <li>
 Experience with enterprise document repositories and their integration APIs.
 </li>
 <li>
 Familiarity with Azure AI Studio and custom model deployment.
 </li>
 <li>
 Exposure to distributed processing frameworks for large-scale batch operations.
 </li>
 <li>
 Strong communication skills for client-facing technical discussions.
 
 </li>
 </ul>
</div>

AI Architect - Big Entities

Tata Consultancy Services (TCS)

<div></div><div><div><div><div>TCS Walk-in Drive at Hyderabad- Synergy Park

Date- 11-Apr-26

JD

<div><div><div><div><div>Skills and Experience Required</div> 
</div><div><ul><li> 15+ years of overall experience in architecting and building data and analytics solutions</li></ul>
<ul><li> Proven hands-on experience in architecting and implementing solutions using leading cloud data platforms like Databricks, Snowflake, Microsoft Fabric etc.</li></ul>
<ul><li> Strong background in designing and implementing ETL/ELT processes, data lakes, and data warehouses</li></ul>
<ul><li> Strong knowledge and experience in building data quality and metadata management solutions.</li></ul>
<ul><li> Experience with one or more major cloud platforms (Azure, AWS, GCP), with a preference for Azure and its data services ecosystem</li></ul>
<ul><li> Familiarity with Spark, Hadoop, and streaming data technologies</li></ul>
<ul><li> Familiarity with CI/CD pipelines, automation, and infrastructure-as-code</li></ul>
<ul><li> Experienced in working in a customer-facing role</li></ul>
<ul><li> Certifications in Databricks, Snowflake, Microsoft are preferred</li></ul> 
</div></div> 
<div><div><div>Responsibilities</div> 
</div><div><ul><li> Design, build, and maintain scalable, secure, and high-performance data architectures on cloud platforms such as Databricks, Snowflake, and Microsoft Fabric</li></ul>
<ul><li> Lead migration and modernization of legacy data systems</li></ul>
<ul><li> Collaborate with data engineers, analysts, and business stakeholders to translate business requirements into robust data solutions</li></ul>
<ul><li> Establish and enforce data governance, quality, and security standards across the cloud data ecosystem</li></ul>
<ul><li> Evaluate emerging technologies and recommend best-fit solutions to enhance the organization&rsquo;s data capabilities</li></ul>
<ul><li> Document data architecture designs, workflows, and standards for technical and non-technical audiences</li></ul>
<ul><li> Mentor and guide junior team members on best practices and new technologies in the cloud data space</li></ul>
<ul><li> Stay current with industry trends, certifications, and advancements in cloud data platforms and analytics</li></ul> 
</div></div> 
</div></div> 
</div></div></div><div><div><div>Location</div>
<div>Hyderabad</div>
</div><div><div>Job Function</div>
<div>TECHNOLOGY</div>
</div><div><div>Role</div>
<div>Developer</div>
</div><div><div>Job Id</div>
<div>405017</div>
</div><div><div>Desired Skills</div>
<div>AWS | Azure | Spark | SNOW</div>
</div></div>Desired Candidate Profile
<div><div>Qualifications : BACHELOR OF TECHNOLOGY</div></div></div><div></div>

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