data engineer

senior data engineer

business analyst

data analyst

data scientist

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>
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Data Architect

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>

H2o Labs

Location: Onsite Shift: Night Shift Job Type: Full-TimeJob Overview:We are looking for a skilled and detail-oriented Data Engineer with 2&ndash;4 years of hands-on experience to join our growing team. The ideal candidate will be responsible for building, optimizing, and maintaining scalable data pipelines and architectures to support data-driven decision-making across the organization.Key Responsibilities:<ul><li>Design, develop, and maintain scalable ETL/ELT pipelines</li><li>Build and manage data warehouses and data lakes</li><li>Ensure data quality, integrity, and reliability across systems</li><li>Optimize and automate data workflows for performance and scalability</li><li>Collaborate with data analysts, scientists, and business stakeholders</li><li>Work with large datasets and ensure efficient data processing</li><li>Monitor and troubleshoot data-related issues</li><li>Implement data security and governance best practices</li><li>Communicate effectively with cross-functional teams and stakeholders</li></ul>Required Skills &amp; Qualifications:<ul><li>Bachelor&rsquo;s degree in Computer Science, IT, or related field</li><li>2&ndash;4 years of experience as a Data Engineer or similar role</li><li>Strong proficiency in SQL and database design</li><li>Hands-on experience with Python (or similar programming language)</li><li>Experience with ETL tools (e.g., Airflow, Talend, Informatica)</li><li>Familiarity with cloud platforms (AWS, GCP, or Azure)</li><li>Experience with big data tools (e.g., Hadoop, Spark)</li><li>Understanding of data warehousing concepts</li><li>Excellent communication and interpersonal skills</li><li>Strong problem-solving and analytical skills</li></ul>Preferred Qualifications:<ul><li>Experience with real-time data processing</li><li>Knowledge of Docker/Kubernetes</li><li>Familiarity with CI/CD pipelines</li><li>Experience working in agile environments</li></ul>Job Type: Full-timePay: Rs100,000.00 - Rs220,000.00 per monthWork Location: In person

Data Engineer

Datamatics Technologies

<div>
 Job Title: AI Architect
 
 
 Level:
 
 Senior / Principal
 
 
 Employment Type:
 
 Full-time
 
 
 Experience
 
 : 6+ Years
 
 
 Location
 
 : Islamabad (Onsite)
 
 Role Overview
 
 We are seeking a
 
 high-level AI Architect
 
 to serve as a
 
 Senior Solution Architect
 
 for our real-time automation and intelligence ecosystem. This role is both
 
 strategic and hands-on at the architectural level
 
 , acting as a technical mentor and trusted advisor to engineering teams.
 
 
 You will be responsible for defining and evolving the
 
 enterprise architecture
 
 that underpins real-time data processing, automation, and AI/ML workflows. The role requires a visionary mindset, strong problem-solving capability, and the ability to design scalable, future-ready systems that support complex, high-throughput AI use cases.
 
 Key Responsibilities
 
 
 Solution Mentorship &amp; Technical Leadership
 
 
 <ul>
 <li>
 
 Act as a technical authority and mentor for engineering teams
 
 </li>
 <li>
 
 Guide best practices for real-time data streaming, event-driven architectures, and low-latency processing
 
 </li>
 <li>
 
 Review designs and implementations to ensure architectural consistency and technical excellence
 
 </li>
 </ul>
 
 
 Architecture &amp; Gap Analysis
 
 
 <ul>
 <li>
 
 Analyze existing platforms to identify architectural gaps, performance bottlenecks, and scalability risks
 
 </li>
 <li>
 
 Design and propose robust, enterprise-grade architectural improvements
 
 </li>
 <li>
 
 Define target-state architectures aligned with long-term business and AI strategy
 
 </li>
 </ul>
 
 
 System Orchestration &amp; Integration
 
 
 <ul>
 <li>
 
 Design and oversee the integration of distributed systems, messaging platforms, and data pipelines
 
 </li>
 <li>
 
 Ensure seamless, reliable data flow across heterogeneous enterprise systems
 
 </li>
 <li>
 
 Define standards for system interoperability, resilience, and observability
 
 </li>
 </ul>
 
 
 AI/ML Infrastructure &amp; Enablement
 
 
 <ul>
 <li>
 
 Architect the data and compute foundations required for AI/ML workloads, including agentic workflows and real-time analytics
 
 </li>
 <li>
 
 Enable large-scale automation, intelligent decisioning, and near-real-time inference
 
 </li>
 <li>
 
 Ensure architectures support model lifecycle management, scalability, and performance
 
 </li>
 </ul>
 
 
 Technical Governance &amp; Quality
 
 
 <ul>
 <li>
 
 Ensure architectural designs align with industry standards, security requirements, and scalability goals
 
 </li>
 <li>
 
 Provide high-level design documentation, reference architectures, and technical blueprints
 
 </li>
 <li>
 
 Support roadmap definition and continuous architectural evolution
 
 </li>
 </ul>
 Technical Requirements
 <ul>
 <li>
 
 
 Expert-level experience with distributed systems
 
 , including:
 
 <ul>
 <li>
 
 Real-time stream processing
 
 </li>
 <li>
 
 Distributed storage platforms
 
 </li>
 <li>
 
 Low-latency analytical databases
 
 </li>
 </ul>
 </li>
 <li>
 
 Proven experience designing
 
 enterprise-scale, high-throughput data architectures
 
 
 </li>
 <li>
 
 Strong background in
 
 event-driven and real-time processing ecosystems
 
 
 </li>
 <li>
 
 Experience supporting
 
 AI/ML platforms
 
 , data fabrics, and automation frameworks
 
 </li>
 <li>
 
 Demonstrated ability to translate complex technical challenges into scalable architectural solutions
 
 </li>
 </ul>
 Leadership &amp; Soft Skills
 <ul>
 <li>
 
 Strong
 
 mentorship and coaching experience
 
 with senior engineering teams
 
 </li>
 <li>
 
 Ability to influence architectural direction across multiple teams and stakeholders
 
 </li>
 <li>
 
 Excellent communication skills, capable of articulating complex designs to both technical and non-technical audiences
 
 </li>
 <li>
 
 Strategic mindset with a focus on long-term platform evolution
 
 </li>
 </ul>
 Nice to Have
 <ul>
 <li>
 
 Experience with cloud-native and hybrid architectures
 
 </li>
 <li>
 
 Exposure to MLOps, DataOps, or platform engineering practices
 
 </li>
 <li>
 
 Experience in regulated or large enterprise environments
 
 </li>
 </ul>
 Why Join
 <ul>
 <li>
 
 Shape the
 
 architectural foundation of advanced AI and automation platforms
 
 
 </li>
 <li>
 
 Influence enterprise-scale technical decisions with long-term impact
 
 </li>
 <li>
 
 Work in a senior, high-visibility role with strong ownership and autonomy
 
 </li>
 </ul>
</div>

AI Architect

ACE Money Transfer

<div>About Us: 
 
We are a dynamic and fast-growing financial technology group headquartered in Manchester, United Kingdom, with an established presence across the UK, Europe, Canada, Australia, Pakistan, and Bangladesh. Our group, encompassing ACE Money Transfer and ACE Union, operates across two regulated verticals: Electronic Money Services (EMI) and Cross-Border Remittances. 
Through our digital platforms, including mobile apps, web portals, and APIs, we deliver a comprehensive range of regulated financial services. These include digital payments, e-wallets, electronic money issuance, prepaid cards, mobile top-ups, bill payments, and international money transfers, designed to serve both individual and business customers in over 100 countries. By leveraging cutting-edge technologies such as AI for fraud detection, automation for seamless transactions, and partnerships with global leaders like Mastercard, we provide secure, user-friendly, and accessible financial solutions that adapt to the evolving needs of a global customer base. 
As we scale our EMI and remittance operations amid 2025's fintech landscape marked by real-time payments, embedded finance, blockchain integration, and sustainability initiatives, we are building a leadership team to drive innovation, regulatory compliance, and excellence across our dual-regulated ecosystem. 
 
Job Overview:
 
 
This role is focused on designing and delivering scalable, secure, and high-performance data architectures to support the organization&rsquo;s expanding analytical and operational needs. The Senior Data Engineer will work closely with cross-functional teams to understand complex data requirements, define and implement robust data transformation rules, and lead the development and optimization of end-to-end data pipelines and data warehouse infrastructure. 
The ideal candidate will have hands-on experience in API based data integrations with third-party platforms, as well as a strong grasp of data governance principles. This includes implementing policies to ensure data quality, privacy, security, and compliance with regulatory standards. The role also involves optimizing workflows for cost efficiency and performance, while providing technical leadership to engineering and analytics teams in executing complex, data driven initiatives. 
 
Key Responsibilities:<ul><li>
Architecting Scalable Data Systems: Designing robust data infrastructures capable of supporting increasing data volume and complexity.</li><li>
Design Data Pipelines: Develop efficient data ingestion pipelines and ETL processes capable of handling both structured and unstructured data effectively.</li><li>
Data Warehouse Management: Manage and optimize the data warehouse, ensuring efficient data storage, retrieval, and transformation. Implement best practices for organizing and managing raw, processed, and curated data, with scalability and future growth in mind</li><li>
Optimize Data Modelling: Write, optimize, and maintain complex SQL queries and Python scripts to ensure efficient data processing.</li><li>
Streamlining Data Workflows: Enhancing data storage, processing, and access methods to improve efficiency, strengthen data observability, and reduce operational costs through targeted infrastructure optimizations.</li><li>
Governance &amp; Quality: Develop and maintain data quality checks to ensure data is accurate, consistent, and regulatory compliant.</li><li>
Develop Integration Procedures: Design and implement processes to integrate data warehouse solutions into operational IT environments.</li><li>
Driving Technical Leadership: Guiding engineering and analytics teams in the execution of data-driven initiatives and innovation.</li><li>
Research &amp; Development: Keep up with the latest technological trends and identify innovative solutions to address customer challenges and company priorities.</li></ul><div> 

Skills and Qualifications:<ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Engineering, Computer Science, or a related field, or equivalent professional experience.</li><li>
Minimum of 4 years of hands-on experience in a Data Engineering or Data Architecture role.</li><li>
Proven experience with cloud platforms such as AWS, Azure, or GCP, with practical knowledge of their core data and infrastructure services.</li><li>
Proficient in using ETL tools and frameworks such as AWS Glue, Apache Airflow, Apache Spark, Kafka, Informatica, DataStage, or Talend for integrating data from multiple sources.</li><li>
Demonstrated expertise in setting up and managing scalable, high-performance data warehouse environments.</li><li>
Strong understanding of dimensional data modeling and mapping techniques, including Star, Snowflake, and Galaxy schemas.</li><li>
Solid understanding of data privacy regulations, including GDPR, and experience applying best practices for data security, compliance, and governance.</li><li>
Working knowledge of data observability principles and the full data lifecycle management.</li><li>
Extensive experience in designing and developing ETL architectures to support large-scale, distributed data processing.</li><li>
Deep knowledge of relational database concepts and advanced proficiency in SQL and Python for data manipulation and transformation.</li><li>
Experience working in distributed environments, including clustering, partitioning, and sharding strategies.</li><li>
Familiarity with building semantic models and preparing reporting and mapping documentation.</li><li>
Strong analytical and problem-solving skills, with a logical and solution-oriented mindset.</li><li>
Prior experience in the financial services sector is a plus.</li></ul></div>
TxQ5oMMo2d</div>

Senior Data Engineer

Senior / Lead / Data Engineer &ndash; Comprehensive Job DescriptionAbout the RoleWe are seeking a highly skilled and experienced Senior/Lead/Staff Data Engineer todesign, build, and maintain scalable, reliable, and high-performance data systems. Thisrole requires deep technical expertise, strong ownership of data platforms, and the abilityto lead cross-functional initiatives that power analytics, machine learning, businessintelligence, and mission-critical applications.You will play a key role in shaping data architecture, ensuring data quality and governance,and enabling teams across the organization to make data-driven decisions withconfidence.Key ResponsibilitiesData Architecture &amp; Modeling<ul><li>Design and implement scalable data models, including:</li></ul>o Star schema (fact and dimension tables)o Conceptual, logical, and physical data models<ul><li>Develop enterprise data warehouse solutions ensuring:</li></ul>o Flexibility, scalability, and performance optimization<ul><li>Define and enforce data modeling standards and best practices</li></ul>Data Engineering &amp; Pipeline Development<ul><li>Build and maintain end-to-end data pipelines:</li></ul>o Data ingestion &rarr; staging &rarr; transformation &rarr; serving layers<ul><li>Develop robust ETL/ELT processes using modern tools and frameworks</li><li>Implement:</li></ul>o Typed staging layerso Data validation pipelineso Safe backfill and replay mechanisms<ul><li>Optimize SQL queries, indexing strategies, and database performanceData Platform Reliability &amp; Observability</li><li>Own data pipeline reliability and integrity</li><li>Build observability systems, including:</li></ul>o Monitoring dashboardso Alerting frameworks (actionable, low-noise)o Data freshness tracking<ul><li>Implement:</li></ul>o Schema contracts and enforcemento Data quality checks and validation ruleso Failure detection in CI pipelines (not post-deployment)<ul><li>Lead incident management and root cause analysis</li></ul>Data Governance &amp; Quality<ul><li>Establish data governance frameworks:</li></ul>o Standards, policies, and best practices<ul><li>Enforce:</li></ul>o Data integrityo Data lineage and traceabilityo Access controls and compliance<ul><li>Separate and maintain clear boundaries between:</li></ul>o Core governed datasetso Downstream analytics/BI layersCloud &amp; Big Data Integration<ul><li>Integrate systems with:</li></ul>o Data lakes and large-scale data platforms<ul><li>Work with modern cloud ecosystems (AWS preferred):</li></ul>oo Data warehouse platforms (e.g., Redshift, Snowflake)<ul><li>Design cost-efficient and scalable data solutions</li></ul>Analytics Engineering &amp; Data Products<ul><li>Design and deliver data products used by:</li></ul>o Analystso Data scientistso Product teams<ul><li>Build reusable frameworks for:</li></ul>o Data transformationo Orchestrationo Feature engineering (ML readiness)<ul><li>Support advanced analytics and reporting use cases</li></ul>CI/CD &amp; DevOps for Data<ul><li>Implement CI/CD pipelines for data workflows</li><li>Automate:</li></ul>o Testingo Deploymento Validation<ul><li>Use version control systems (Git/GitHub)</li><li>Ensure:</li></ul>o High availabilityo Backup and recovery strategiesProgramming &amp; Tooling<ul><li>Develop solutions using:</li></ul>oo Python (automation, validation, tooling)<ul><li>Work with tools such as:</li></ul>o dbt (deep experience required)o DBeaver, Visual Studioo Orchestration tools (e.g., Dagster or similar)Leadership &amp; Collaboration<ul><li>Lead cross-functional technical initiatives</li><li>Mentor and guide junior to mid-level data engineers</li><li>Conduct:</li></ul>o Code reviewso Architecture discussionso Knowledge sharing sessions<ul><li>Collaborate with:</li></ul>o Engineering teamso Product managerso Business stakeholders<ul><li>Translate business requirements into scalable data solutions</li></ul>Strategic Impact<ul><li>Drive platform evolution and innovation</li><li>Identify opportunities for:</li></ul>o Performance improvementso Cost optimization (FinOps mindset)o Automation and scalability<ul><li>Influence organizational data strategy and roadmapRequired Qualifications</li><li>Bachelor&rsquo;s degree in computer science, Engineering, IT, or related field</li><li>4&ndash;5+ years of experience in data engineering or analytics engineering</li><li>Strong expertise in:</li></ul>o Data modeling (star schema, dimensional modeling)o SQL and performance tuningo ETL/ELT pipeline development<ul><li>Hands-on experience with:</li></ul>o Data warehousing and data lakeso Big data integrations<ul><li>Experience with:</li></ul>o Cloud platforms (AWS preferred)o Data quality, validation, and governance frameworks<ul><li>Strong understanding of:</li></ul>o System designo Scalable architecture<ul><li>Excellent communication and stakeholder management skills</li><li>Ability to work in agile, fast-paced environments</li><li>Eligibility to obtain security clearance (if required)</li></ul>Preferred Qualifications<ul><li>Experience with:</li></ul>o AWS services (Glue, Lambda, etc.)o Snowflake, Redshifto dbt (production-level deployments)<ul><li>Knowledge of:</li></ul>o Machine learning data pipelineso Certifications:o SQL Server, CDMP, MCSA, or similar<ul><li>Experience in:</li></ul>o Healthcare, defense, or regulated industries<ul><li>Familiarity with:</li></ul>o CI/CD for data systemso Data governance and FinOps practicesWhat Makes a Strong Candidate<ul><li>Thinks of systems, not just pipelines</li><li>Focuses on root-cause solutions, not temporary fixes</li><li>Balances:</li></ul>o Business valueo Scalabilityo Maintainability<ul><li>Strong ownership mindset with ability to lead initiatives end-to-end</li><li>Passion for building resilient, high-quality data platforms</li></ul>Job Type: Full-timePay: Rs250,000.00 - Rs350,000.00 per monthWork Location: In person

Lead Data Engineer

ACE Union

About Us:We are a dynamic and fast-growing financial technology group headquartered in Manchester, United Kingdom, with an established presence across the UK, Europe, Canada, Australia, Pakistan, and Bangladesh. Our group, encompassing ACE Money Transfer and ACE Union, operates across two regulated verticals: Electronic Money Services (EMI) and Cross-Border Remittances.Through our digital platforms, including mobile apps, web portals, and APIs, we deliver a comprehensive range of regulated financial services. These include digital payments, e-wallets, electronic money issuance, prepaid cards, mobile top-ups, bill payments, and international money transfers, designed to serve both individual and business customers in over 100 countries. By leveraging cutting-edge technologies such as AI for fraud detection, automation for seamless transactions, and partnerships with global leaders like Mastercard, we provide secure, user-friendly, and accessible financial solutions that adapt to the evolving needs of a global customer base.As we scale our EMI and remittance operations amid 2025's fintech landscape, marked by real-time payments, embedded finance, blockchain integration, and sustainability initiatives, we are building a leadership team to drive innovation, regulatory compliance, and excellence across our dual-regulated ecosystem.Job Overview: This role is focused on designing and delivering scalable, secure, and high-performance data architectures to support the organization&rsquo;s expanding analytical and operational needs. The Senior Data Engineer will work closely with cross-functional teams to understand complex data requirements, define and implement robust data transformation rules, and lead the development and optimization of end-to-end data pipelines and data warehouse infrastructure. The ideal candidate will have hands-on experience in API based data integrations with third-party platforms, as well as a strong grasp of data governance principles. This includes implementing policies to ensure data quality, privacy, security, and compliance with regulatory standards. The role also involves optimizing workflows for cost efficiency and performance, while providing technical leadership to engineering and analytics teams in executing complex, data driven initiatives.Key Responsibilities:<ul><li>Architecting Scalable Data Systems: Designing robust data infrastructures capable of supporting increasing data volume and complexity.</li><li>Design Data Pipelines: Develop efficient data ingestion pipelines and ETL processes capable of handling both structured and unstructured data effectively.</li><li>Data Warehouse Management: Manage and optimize the data warehouse, ensuring efficient data storage, retrieval, and transformation. Implement best practices for organizing and managing raw, processed, and curated data, with scalability and future growth in mind</li><li>Optimize Data Modelling: Write, optimize, and maintain complex SQL queries and Python scripts to ensure efficient data processing.</li><li>Streamlining Data Workflows: Enhancing data storage, processing, and access methods to improve efficiency, strengthen data observability, and reduce operational costs through targeted infrastructure optimizations.</li><li>Governance &amp; Quality: Develop and maintain data quality checks to ensure data is accurate, consistent, and regulatory compliant.</li><li>Develop Integration Procedures: Design and implement processes to integrate data warehouse solutions into operational IT environments.</li><li>Driving Technical Leadership: Guiding engineering and analytics teams in the execution of data-driven initiatives and innovation.</li><li>Research &amp; Development: Keep up with the latest technological trends and identify innovative solutions to address customer challenges and company priorities.</li></ul>Skills and Qualifications:<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Engineering, Computer Science, or a related field, or equivalent professional experience.</li><li>Minimum of 4 years of hands-on experience in a Data Engineering or Data Architecture role.</li><li>Proven experience with cloud platforms such as AWS, Azure, or GCP, with practical knowledge of their core data and infrastructure services.</li><li>Proficient in using ETL tools and frameworks such as AWS Glue, Apache Airflow, Apache Spark, Kafka, Informatica, DataStage, or Talend for integrating data from multiple sources.</li><li>Demonstrated expertise in setting up and managing scalable, high-performance data warehouse environments.</li><li>Strong understanding of dimensional data modeling and mapping techniques, including Star, Snowflake, and Galaxy schemas.</li><li>Solid understanding of data privacy regulations, including GDPR, and experience applying best practices for data security, compliance, and governance.</li><li>Working knowledge of data observability principles and the full data lifecycle management.</li><li>Extensive experience in designing and developing ETL architectures to support large-scale, distributed data processing.</li><li>Deep knowledge of relational database concepts and advanced proficiency in SQL and Python for data manipulation and transformation.</li><li>Experience working in distributed environments, including clustering, partitioning, and sharding strategies.</li><li>Familiarity with building semantic models and preparing reporting and mapping documentation.</li><li>Strong analytical and problem-solving skills, with a logical and solution-oriented mindset.</li><li>Prior experience in the financial services sector is a plus.</li></ul>Job Type: Full-timePay: Rs300,000.00 - Rs350,000.00 per monthApplication Question(s):<ul><li>The shift timing connected with the role is 01:00 PM PST to 10:00 PM PST. Is it feasible for you to work in these timings?</li><li>Is it possible for you to commute daily to Gulberg-3 Lahore, or to relocate to Lahore city for this job?</li><li>What is your current salary package?</li><li>What is your expected salary?</li></ul>Experience:<ul><li>Data Engineering or Data Architecture: 4 years (Required)</li></ul>Language:<ul><li>English proficiently (Required)</li></ul>Work Location: In person

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767 data architect jobs In Lahore

Data Architect

Data Architect

Data Engineer

AI Architect

Senior Data Engineer

Lead Data Engineer

Senior Data Engineer