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software quality assurance engineer

data warehouse engineer

ByteCrew

<div>
 
 Role Summary
 
 
 
 About the job Data Engineer
 
 
 We are seeking a Data Engineer to design, build, and operate data pipelines and warehouses powering
 
 
 enterprise analytics and reporting. The role covers ingestion, transformation, modelling, and operationalisation
 
 
 across cloud and on-prem data sources.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design and implement batch + streaming data pipelines (ETL/ELT).
 </li>
 <li>
 Build and maintain dimensional/data-warehouse models (Star/Snowflake schema, slowly-changing
 
 
 </li>
 </ul>
 dimensions).
 
 
 <ul>
 <li>
 Develop in SQL, Python, and at least one orchestrator (Airflow, Azure Data Factory, AWS Glue).
 </li>
 <li>
 Operate data quality checks, lineage, and observability (Great Expectations, Monte Carlo, or similar).
 </li>
 <li>
 Optimise warehouse performance (Snowflake, Synapse, BigQuery, Redshift).
 </li>
 <li>
 Partner with BI/analytics teams on semantic models and self-service consumption.
 </li>
 <li>
 Document pipelines, schemas, and runbooks.
 
 
 </li>
 </ul>
 
 Required Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's degree in CS, Engineering, Statistics, or equivalent.
 </li>
 <li>
 4+ years building production data pipelines.
 </li>
 <li>
 Strong SQL (window functions, CTEs, query tuning) and Python.
 </li>
 <li>
 Hands-on with at least one major DW/Lakehouse: Snowflake, BigQuery, Synapse, Redshift, Databricks.
 </li>
 <li>
 Experience with at least one orchestrator: Airflow, ADF, Glue, dbt + scheduler.
 </li>
 <li>
 Familiarity with cloud object storage (S3, ADLS, GCS) and file formats (Parquet, ORC, Avro).
 </li>
 <li>
 Professional English &mdash; mandatory.
 
 
 </li>
 </ul>
 
 Preferred / Nice To Have
 
 
 
 <ul>
 <li>
 Working knowledge of Arabic is a plus.
 </li>
 <li>
 Streaming experience: Kafka, Kinesis, Event Hubs, Spark Structured Streaming.
 </li>
 <li>
 dbt Analytics Engineer or cloud data engineer certifications.
 </li>
 <li>
 Exposure to data governance/cataloguing (Purview, Unity Catalog, Collibra).
 </li>
 </ul>
</div>

Data Engineer
Lahore, Pakistan

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

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

HireOn

<div>
 
 Employment Type:
 
 Full-Time | Permanent
 
 
 
 Location:
 
 Pakistan (Lahore / Karachi / Islamabad) &ndash; Hybrid
 
 
 
 About The Opportunity
 
 
 
 
 HireOn
 
 is hiring on behalf of a
 
 reputed international client
 
 seeking a
 
 Principal Data Engineer
 
 to play a pivotal role in building and scaling a next-generation cloud data platform.
 
 
 This position focuses on designing and delivering
 
 high-performance data pipelines and warehouse solutions on Amazon Redshift
 
 , enabling faster analytics, improved reliability, and scalable data operations.
 
 
 You will take ownership of
 
 architecting data workflows, optimizing processing performance, and implementing production-grade orchestration
 
 , while collaborating with cross-functional teams to drive data-driven outcomes.
 
 
 
 Key Requirements (Must-Have First)
 
 
 
 <ul>
 <li>
 6 to 8+ years of experience in data engineering, data platforms, or data warehousing
 </li>
 <li>
 Advanced expertise in Amazon Redshift, including performance tuning, workload optimization, and MPP architecture
 </li>
 <li>
 Strong hands-on experience with Apache Airflow (MWAA preferred) for workflow orchestration
 </li>
 <li>
 Proficiency in SQL and Python for building scalable data pipelines
 </li>
 <li>
 Solid experience with cloud-based data ecosystems on AWS (S3, Lambda, CloudWatch, DMS)
 </li>
 <li>
 Deep understanding of data modeling, ETL/ELT frameworks, and large-scale data processing
 </li>
 <li>
 Proven ability to design high-performance, distributed data pipelines
 </li>
 <li>
 Experience leading engineering efforts, including code reviews, mentoring, and technical decision-making
 </li>
 <li>
 Strong knowledge of query optimization, parallel processing, and data pipeline efficiency
 
 
 </li>
 </ul>
 
 
 Core Technical Skills
 
 
 
 
 
 Essential
 
 
 
 <ul>
 <li>
 Amazon Redshift (Provisioned / Serverless)
 </li>
 <li>
 MPP data processing concepts
 </li>
 <li>
 Apache Airflow (MWAA)
 </li>
 <li>
 Advanced SQL &amp; performance tuning
 </li>
 <li>
 Python for data engineering
 </li>
 <li>
 Data modeling &amp; warehousing concepts
 
 
 </li>
 </ul>
 
 Preferred
 
 
 
 <ul>
 <li>
 AWS services (S3, Lambda, DMS, Aurora PostgreSQL)
 </li>
 <li>
 CI/CD pipelines &amp; Git-based workflows
 </li>
 <li>
 Linux/Unix environments
 </li>
 <li>
 Experience with large-scale, distributed data systems
 
 
 </li>
 </ul>
 
 What Success Looks Like
 
 
 
 <ul>
 <li>
 Highly optimized and scalable data pipelines running on Redshift
 </li>
 <li>
 Reliable orchestration with minimal downtime and strong observability
 </li>
 <li>
 Efficient handling of large datasets with improved query performance
 </li>
 <li>
 Well-architected data platform aligned with modern engineering standards
 
 
 </li>
 </ul>
 
 
 Why Join Through HireOn
 
 
 
 
 <ul>
 <li>
 Opportunity to work with a globally recognized client on high-impact data initiatives
 </li>
 <li>
 Exposure to modern cloud data technologies and large-scale systems
 </li>
 <li>
 Hybrid work flexibility within Pakistan
 </li>
 <li>
 Career growth into data architecture and platform leadership roles
 
 
 </li>
 </ul>
 Skills: apache airflow,python,plsql,aws,amazon redshift
</div>

Principal Data Engineer – AWS Redshift & Data Platforms

HR POD Careers

<div>
 
 
 Requirements:
 
 
 
 
 <ul>
 <li>
 3+ years of experience in Data Engineering or related roles.
 </li>
 <li>
 Strong expertise in SQL, query optimization, and database performance tuning.
 </li>
 <li>
 Proven experience in designing, building, and maintaining ETL/ELT pipelines.
 </li>
 <li>
 Hands-on experience with Databricks or similar large-scale data processing platforms.
 </li>
 <li>
 Experience working with cloud data warehouses such as Snowflake, BigQuery, or Redshift.
 </li>
 <li>
 Proficiency in Python for data processing, scripting, and automation.
 </li>
 <li>
 Familiarity with workflow orchestration tools such as Airflow or similar platforms.
 </li>
 <li>
 Strong understanding of data modeling, data warehousing, and scalable architecture design.
 </li>
 <li>
 Experience handling large datasets and distributed data systems.
 </li>
 <li>
 Excellent problem-solving, troubleshooting, and debugging skills.
 </li>
 <li>
 Experience with Spark, Kafka, or real-time data streaming technologies.
 </li>
 <li>
 Exposure to healthcare or SaaS-based datasets is a plus.
 </li>
 <li>
 Knowledge of data governance, metadata management, and data quality practices.
 </li>
 <li>
 Familiarity with DevOps practices, CI/CD pipelines, and infrastructure automation.
 </li>
 <li>
 Experience supporting and maintaining machine learning pipelines.
 
 
 
 </li>
 </ul>
 
 
 Responsibilities:
 
 
 
 
 <ul>
 <li>
 Design, develop, and maintain scalable ETL/ELT pipelines using internal systems, APIs, and external data sources.
 </li>
 <li>
 Build and optimize data architectures, warehouses, and storage solutions for scalability and performance.
 </li>
 <li>
 Clean, validate, and transform raw data to support analytics, reporting, and business intelligence needs.
 </li>
 <li>
 Write, optimize, and maintain complex SQL queries and data models.
 </li>
 <li>
 Monitor and manage data workflows to ensure performance, reliability, and scalability.
 </li>
 <li>
 Ensure data quality, integrity, consistency, and security across all systems and pipelines.
 </li>
 <li>
 Collaborate closely with analysts and stakeholders to support reporting and business intelligence requirements.
 </li>
 <li>
 Automate repetitive data processes and continuously improve workflow efficiency.
 </li>
 <li>
 Maintain clear documentation for data pipelines, datasets, schemas, and infrastructure.
 </li>
 <li>
 Continuously evaluate and enhance the company's data stack, architecture, and engineering best practices.
 
 </li>
 </ul>
</div>

Data Engineer (Onsite, Lahore, PKR Salary)

H2o Labs

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

About the RoleWe are seeking a highly skilled and experienced Senior / Lead Data Engineer to design, build, and maintain scalable, reliable, and high-performance data systems.In this role, you will take ownership of data platforms, lead cross-functional initiatives, and enable analytics, machine learning, and business intelligence across the organization. You will play a key role in shaping data architecture, ensuring data quality and governance, and supporting data-driven decision-making.Key ResponsibilitiesData Architecture &amp; Modeling<ul><li>Design and implement scalable data models (star schema, fact/dimension tables)</li><li>Develop conceptual, logical, and physical data models</li><li>Build enterprise data warehouse solutions with high performance and scalability</li><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 (ingestion &rarr; transformation &rarr; serving)</li><li>Develop ETL/ELT processes using modern tools and frameworks</li><li>Implement data validation pipelines and staging layers</li><li>Optimize SQL queries, indexing, and database performance</li></ul>Data Platform Reliability &amp; Observability<ul><li>Ensure reliability and integrity of data pipelines</li><li>Build monitoring dashboards and alerting systems</li><li>Implement data quality checks and schema enforcement</li><li>Lead incident management and root cause analysis</li></ul>Data Governance &amp; Quality<ul><li>Establish data governance frameworks and policies</li><li>Ensure data integrity, lineage, and compliance</li><li>Manage access controls and data security</li><li>Maintain separation between core datasets and analytics layers</li></ul>Cloud &amp; Big Data Integration<ul><li>Integrate systems with data lakes and large-scale platforms</li><li>Work with cloud environments (AWS preferred)</li><li>Utilize tools such as AWS Glue, Lambda, Redshift, or Snowflake</li><li>Design scalable and cost-efficient data solutions</li></ul>Analytics Engineering &amp; Data Products<ul><li>Build and deliver data products for analysts and data scientists</li><li>Develop reusable frameworks for transformation and orchestration</li><li>Support advanced analytics and reporting</li></ul>CI/CD &amp; DevOps for Data<ul><li>Implement CI/CD pipelines for data workflows</li><li>Automate testing, deployment, and validation</li><li>Use version control tools (Git/GitHub)</li><li>Ensure high availability and disaster recovery</li></ul>Programming &amp; Tools<ul><li>Strong expertise in SQL (advanced level)</li><li>Proficiency in Python for automation and data processing</li><li>Experience with tools such as dbt, DBeaver, and orchestration tools (e.g., Dagster)</li></ul>Leadership &amp; Collaboration<ul><li>Lead technical initiatives and mentor junior engineers</li><li>Conduct code reviews and architecture discussions</li><li>Collaborate with engineering, product, and business teams</li><li>Translate business requirements into scalable data solutions</li></ul>Requirements<ul><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 related roles</li><li>Strong expertise in data modeling, SQL, and ETL/ELT pipelines</li><li>Experience with data warehousing and data lakes</li><li>Hands-on experience with cloud platforms (AWS preferred)</li><li>Strong understanding of system design and scalable architecture</li><li>Excellent communication and stakeholder management skills</li><li>Ability to work in fast-paced, agile environments</li></ul>Preferred Qualifications<ul><li>Experience with AWS services (Glue, Lambda, etc.)</li><li>Experience with Snowflake or Redshift</li><li>Strong hands-on experience with dbt</li><li>Knowledge of machine learning data pipelines</li><li>Certifications (SQL Server, CDMP, MCSA, or similar)</li><li>Experience in regulated industries (Healthcare, Defense, etc.)</li><li>Familiarity with CI/CD, data governance, and FinOps practices</li></ul>Job Type: Full-timePay: Rs250,000.00 - Rs400,000.00 per monthWork Location: In person

Explore 596+ Data warehouse engineer in Lahore this May. Find roles across top companies and apply now to boost your career.

596 data warehouse engineer jobs In Lahore

Data Engineer Lahore, Pakistan

Senior Data Engineer

Senior Data Engineer

Principal Data Engineer – AWS Redshift & Data Platforms

Data Engineer (Onsite, Lahore, PKR Salary)

Lead Data Engineer

Senior Data Engineer