data scientist

data analyst

ai engineer

senior data engineer

qa engineer

data engineer

ZIEL Global Private Limited

About the Role We&rsquo;re looking for a Data Engineer to build secure, reliable, and scalable data pipelines powering real-time analytics and AI insights. You&rsquo;ll design cloud-based architectures that process, clean, and deliver mission-critical data across operations.Key Responsibilities<ul><li>Design and maintain data pipelines for large-scale transactional and real-time data</li><li>Develop ETL/ELT workflows using Azure Data Factory, Databricks, or similar</li><li>Implement data quality, validation, and monitoring frameworks</li><li>Ensure compliance with data governance and protection regulations</li><li>Optimize data storage and access performance</li><li>Collaborate with AI, product, and backend teams for seamless data delivery</li></ul>Qualifications<ul><li>Bachelor&rsquo;s in Computer Science, Engineering, or related field</li><li>5+ years of data engineering experience</li><li>Expertise in SQL, Python, and Azure data services (Data Factory, Synapse, Data Lake)</li><li>Knowledge of both batch and streaming architectures</li><li>Strong understanding of data security and governance</li></ul>Preferred<ul><li>Experience with real-time analytics and industrial or procurement datasets</li></ul>Job Type: Full-timeApplication Question(s):<ul><li>Are you available to join immediately?</li><li>How would you rate your English communication skills, spoken and written?</li><li>What are your salary expectations?</li></ul>Work Location: In person

Data Engineer

Pivotize Consulting

Position Overview:We are seeking a experienced Data Engineer to join the team. As a Data Engineer, you will play a crucial role in designing, implementing, and maintaining the infrastructure necessary for our data initiatives, ensuring scalability, reliability, and efficiency. You will collaborate with cross-functional teams to develop robust data pipelines, optimize data workflows, and ensure the reliability and scalability of our data systems.Key Responsibilities:&middot; Develop and maintain ETL (Extract, Transform, Load) processes to integrate data from disparate sources into SQL Server databases.&middot; Write complex SQL queries, stored procedures, and optimize database performance for large-scale datasets.&middot; Develop and implement efficient data models to support analytical and reporting requirements.&middot; Design, implement, and optimize database structures, stored procedures, queries, and views for performance and scalability.&middot; Design and implement database schemas, tables, indexes, Triggers and constraints to ensure efficient storage and retrieval of data.&middot; Perform database debugging, troubleshooting, and bug fixing to identify and resolve issues related to data integrity, performance, and functionality.&middot; Troubleshoot and resolve database issues, including performance bottlenecks, data corruption, and system errors.&middot; Collaborate with cross-functional teams, including software developers, analysts, and business stakeholders, to gather requirements and implement database solutions.&middot; Implement security measures and access controls to protect sensitive data stored in SQL Server databases, in compliance with regulatory requirements and industry best practices.Requirements:&middot; Degree in Computer Science, Engineering, or a related field.&middot; Strong expertise in Microsoft SQL Server (T-SQL, indexing, query tuning, performance optimization).&middot; 5+ years of experience as a Data Engineer or similar role, with a strong background in data warehousing, ETL, and database technologies.&middot; Can demonstrate experience working with large and complex data sets as well as experience analyzing volumes of data.&middot; Experience with monitoring and optimizing database performance in production environments.&middot; Familiarity with cloud-based data architecture and pipelines.&middot; Strong problem-solving, analytical, and debugging skills.&middot; Ability to analyze complex data sets and design scalable data solutions.&middot; Excellent communication and collaboration skills.Job Type: Full-timeApplication Question(s):<ul><li>what is your current salary?</li><li>what is your expected salary?</li><li>What is your notice period?</li><li>Since it's an onsite role, would you be able to commute to Bahria Complex 1, M.T. Khan Road?</li></ul>Work Location: In person

digital.enterprises

<div>
 
 Data Engineer - Build the Data Backbone of ADAPT
 
 
 
 
 About Digital.enterprises
 
 
 
 digital.enterprises is shaping the future of the energy sector.
 
 
 We help companies run smarter integrating people, data, and technology to create intelligent, adaptive, and human-centred operations.
 
 
 Based in Doha, the gas capital of the world, we bring deep industry expertise together with cutting-edge digital thinking to transform how energy companies work, connect, and grow.
 
 
 If youre driven by impact, speed, and purpose not titles or bureaucracy youll fit right in.
 
 
 
 About ADAPT
 
 
 
 ADAPT is our flagship digital platform a real-time digital mesh connecting the energy sectors Maintenance, Repair &amp; Operations (MRO) ecosystem.
 
 
 It replaces slow, fragmented processes with real-time intelligence and automation, connecting operators, contractors, and suppliers through live data, adaptive analytics, and secure, human-in-the-loop governance.
 
 
 Built on Microsoft cloud and AI, ADAPT delivers visibility, intelligence, and agility at industrial scale redefining how energy companies collaborate and compete.
 
 
 
 About The Role
 
 
 
 We are hiring a Data Engineer to design and build secure, scalable data infrastructure for the energy sector. This role focuses on developing robust, high-performance data solutions that enable seamless connectivity across the supply chain from urgent maintenance events to complex planned turnarounds.
 
 
 You will help create the real-time data foundation that powers ADAPT, providing instant visibility and insights that drive smarter, faster, and safer decisions in mission-critical environments.
 
 
 The ideal candidate will have at least five years professional experience and demonstrate excellence in building well-documented, secure, and reliable data solutions that underpin digital transformation at scale.
 
 
 
 Key Responsibilities
 
 
 
 Data Pipeline Development &amp; Optimisation
 
 
 <ul>
 <li>
 Design and implement highly optimised pipelines for processing large-scale supply-chain data supplier performance, inventory, procurement transactions, and real-time equipment status.
 </li>
 <li>
 Develop maintainable ETL/ELT processes supporting both planned and emergency operations, with emphasis on code reusability and long-term stability for 24/7 uptime.
 </li>
 <li>
 Optimise performance to ensure sub-second response for live dashboards and supplier availability.
 </li>
 <li>
 Build automated data-quality frameworks to validate supplier qualifications, inventory accuracy, and compliance data essential to safety and reliability.
 </li>
 <li>
 Support real-time analytics through streaming data pipelines powering live operational intelligence.
 
 
 
 </li>
 </ul>
 Security &amp; Compliance
 
 
 <ul>
 <li>
 Implement strong data-security controls encryption, access management, and masking.
 </li>
 <li>
 Design and enforce data-governance policies aligned with international standards (GDPR, HIPAA, etc.).
 </li>
 <li>
 Conduct regular security audits and vulnerability assessments of data systems.
 </li>
 <li>
 Apply row- and column-level security to protect sensitive data where required.
 
 
 
 </li>
 </ul>
 
 
 
 Azure Cloud Infrastructure
 
 
 
 
 
 <ul>
 <li>
 Architect and maintain data solutions using Azure Data Factory, Databricks, Synapse Analytics, and Data Lake Storage.
 </li>
 <li>
 Integrate Azure Key Vault, Active Directory, and managed identities for secure operations.
 </li>
 <li>
 Optimise Azure resources for cost efficiency and performance.
 </li>
 <li>
 Design and implement backup and disaster-recovery strategies.
 </li>
 <li>
 Leverage Azure Monitor and Application Insights for proactive monitoring and alerting.
 
 
 
 </li>
 </ul>
 
 
 
 Maintainability &amp; Documentation
 
 
 
 
 
 <ul>
 <li>
 Create comprehensive technical documentation for pipelines, architectures, and processes.
 </li>
 <li>
 Maintain detailed runbooks and operational procedures.
 </li>
 <li>
 Implement version control and CI/CD pipelines for data workflows.
 </li>
 <li>
 Document data lineage, transformation logic, and metadata repositories.
 
 
 
 </li>
 </ul>
 
 Communication &amp; Collaboration
 
 
 
 <ul>
 <li>
 Communicate technical concepts clearly to both technical and business stakeholders.
 </li>
 <li>
 Collaborate with developers, analysts, and business teams to translate requirements into data solutions.
 </li>
 <li>
 Provide regular status updates and progress reports to management.
 
 
 
 </li>
 </ul>
 
 System Maintenance &amp; Optimisation
 
 
 
 <ul>
 <li>
 Monitor system health proactively and implement preventive maintenance.
 </li>
 <li>
 Design with maintainability at the core for fast troubleshooting and iteration.
 </li>
 <li>
 Implement automated testing for pipelines.
 </li>
 <li>
 Define and uphold SLAs for data availability and quality.
 </li>
 <li>
 Optimise storage and retention for cost-effectiveness.
 
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 Education &amp; Experience
 
 
 
 <ul>
 <li>
 Bachelors degree in Computer Science, Engineering, or Information Systems.
 </li>
 <li>
 Minimum 5 years professional experience in data engineering or related fields.
 </li>
 <li>
 Proven success designing and implementing enterprise-scale data solutions.
 
 
 
 </li>
 </ul>
 
 Technical Skills
 
 
 
 <ul>
 <li>
 Hands-on expertise with Azure data services Data Factory, Databricks, Synapse Analytics, Data Lake.
 </li>
 <li>
 Proficiency in Python, SQL, Scala, or C#.
 </li>
 <li>
 Experience implementing data-security and access-control mechanisms.
 </li>
 <li>
 Strong knowledge of database-performance optimisation.
 </li>
 <li>
 Proficiency in data-quality and governance frameworks.
 </li>
 <li>
 Understanding of batch and real-time processing architectures.
 
 
 
 </li>
 </ul>
 
 Core Competencies
 
 
 
 <ul>
 <li>
 Documentation excellence: produces clear, thorough, and maintainable documentation.
 </li>
 <li>
 Communication: clear, confident, and adaptable to diverse audiences.
 </li>
 <li>
 Security mindset: embeds data protection into every design decision.
 </li>
 <li>
 Optimisation focus: constantly seeks performance and cost improvements.
 </li>
 <li>
 Maintainability approach: builds systems designed for the long term.
 </li>
 <li>
 Willingness to travel for client implementations and support.
 
 
 
 </li>
 </ul>
 Why Join Us
 
 
 At digital.enterprises, youll help build the data engine that transforms how energy ecosystems operate.
 
 
 Your work will empower people across plants, control rooms, and offices to make decisions in real time supported by data that is secure, trustworthy, and always available.
 
 
 This is your opportunity to contribute to Industry 5.0 in action technology amplifying human capability to deliver safer, cleaner, and more reliable energy for everyone.
</div>

Folio3

<div><div>Ready to design, optimize, and maintain highly scalable data infrastructure? Folio3 is hiring a Data Engineer to lead the development of our ETL/ELT pipelines and advanced cloud data platforms.
<h4 class="jobSectionHeader">
Responsibilities:</h4>
<ul><li>Design and deploy scalable ETL/ELT pipelines using dbt, Airflow, or Azure Data Factory.</li>
<li>Develop integrations between Snowflake, Databricks, and cloud storage layers (S3, ADLS, GCS).</li>
<li>Build data models for analytics and reporting teams.</li>
<li>Implement data quality, lineage, and monitoring frameworks.</li>
<li>Optimize SQL queries, warehouse costs, and job performance.</li>
<li>Collaborate with BI/AI teams for data accessibility and consistency.</li>
<li>Enforce best practices for code versioning, CI/CD, and data governance.</li>
</ul><h4 class="jobSectionHeader">Requirements:</h4>
<ul><li>2-5 years of progressive, hands-on experience in Data Engineering.</li>
<li>Strong SQL and Python (Pandas / PySpark).</li>
<li>Working experience with 2 or more clouds (AWS + Azure / GCP).</li>
<li>Familiar with Snowflake (Snowpipe, Streams/Tasks) or Databricks (Delta Lake, Spark).</li>
<li>Understanding of data orchestration (Airflow, dbt, Dagster).</li>
<li>Basic understanding of DevOps (Docker, GitHub Actions)</li></ul></div></div>

Assurety Consulting & Solutions Pvt. ltd

Assurety Consulting is looking for a skilled Data Engineer to design, develop, and maintain robust data solutions. The ideal candidate will have hands-on experience with SQL Server, SSIS, and Azure Data Factory, along with strong knowledge of ETL processes and data optimization.Key Responsibilities:<ul><li>Develop, optimize, and maintain ETL pipelines and data workflows.</li><li>Work with SQL Server and Azure Data Factory (ADF) for data integration.</li><li>Implement data warehousing, data lake, and data modeling solutions.</li><li>Collaborate with business and analytics teams to ensure reliable data delivery.</li><li>Improve data quality, performance, and scalability.</li></ul>Requirements:<ul><li>Bachelor&rsquo;s degree in Computer Science, Information Systems, or a related field.</li><li>Minimum 3 years of experience as a Data Engineer.</li><li>Strong expertise in SQL Server, SSIS, and Azure Data Factory (ADF).</li><li>Experience in ETL, Data Warehousing, and performance optimization.</li><li>Excellent analytical and problem-solving skills.</li></ul>Why Join Us:<ul><li>Collaborative and growth-oriented work environment.</li><li>Opportunity to work with cutting-edge data technologies.</li><li>Clear career progression paths and skill-building opportunities.</li></ul>Location: Shahrah - e - Faisal, KarachiJob Type: Full-timeWork Location: In person

Horizon Tech

We are looking for a skilled Data Engineer to design, build, and optimise our modern data platform on the cloud. You'll be responsible for architecting scalable, secure, and automated data pipelines and enabling data-driven applications and AI/ML solutions across the organisation.This is an exciting opportunity to shape the data foundation of a growing business, leveraging a modern AWS and engineering ecosystem.Must Haves:<ul><li>3-5 years of experience in data engineering or a similar role working with large-scale, distributed data systems.</li><li>Strong proficiency in Python, SQL, and data modelling for analytical and transactional systems.</li><li>Deep understanding of modern AWS data and analytics services (e.g., S3, Glue, Lambda, Redshift, or equivalents).</li><li>Experience with Apache Spark / PySpark for batch and stream processing.</li><li>Solid knowledge of data governance, security, and compliance frameworks.</li><li>Familiarity with Infrastructure as Code (Terraform, CloudFormation) and CI/CD practices.</li><li>Understanding of AI/ML data workflows, including feature engineering and data preparation for LLMs or predictive models.</li><li>Strong problem-solving, collaboration, and communication skills.</li></ul>Preferred (Nice to Have)<ul><li>Knowledge of containerization (Docker, ECS, EKS) or serverless data architectures.</li><li>Understanding of AI/ML and NLP technologies, including integration of LLMs, automation frameworks, and RPA tools for intelligent data workflows.</li><li>Awareness of MLOps pipelines, model monitoring, and feature store management.</li></ul>Responsibilities:<ul><li>Design, build, and maintain large-scale, distributed, and event-driven data pipelines using modern AWS Data Engineering services (e.g., Glue, Lambda, Step Functions, etc.).</li><li>Develop ETL/ELT workflows integrating structured and unstructured data into Snowflake, Redshift, and S3-based data lakes.</li><li>Architect and optimise data ingestion, transformation, and storage layers for structured and unstructured data in a data lake or warehouse environment.</li><li>Implement and enforce data security, governance, and access controlincluding encryption, IAM, auditing, and compliance with best practices.</li><li>Develop and maintain metadata management, data lineage, and cataloguing frameworks to ensure traceability and consistency across datasets.</li><li>Automate infrastructure provisioning using Infrastructure-as-Code (IaC) tools such as Terraform or AWS CloudFormation.</li><li>Collaborate with analytics and AI/ML teams to deliver clean, high-quality, and feature-ready data for training and inference pipelines.</li><li>Integrate observability and monitoring into data workflows to ensure reliability, performance, and cost efficiency.</li><li>Contribute to CI/CD pipelines and Git-based version control for data workflows and infrastructure changes.</li><li>Mentor junior engineers and champion engineering best practices for data quality, reliability, and scalability.</li></ul>Other Details<ul><li>Work Days: Monday-Friday (3 pm - 12 am)</li><li>Office location: Off to Shahrah-e-Faisal, PECHS, Karachi</li></ul>Job Type: Full-timePay: Rs150,000.00 - Rs250,000.00 per monthApplication Question(s):<ul><li>What is your expected salary?</li></ul>Education:<ul><li>Bachelor's (Required)</li></ul>Experience:<ul><li>data engineering with large-scale data systems: 3 years (Required)</li><li>Python, SQL and modern AWS data and analytics services: 3 years (Required)</li><li>ETL/ELT workflows : 3 years (Required)</li></ul>Location:<ul><li>Karachi (Required)</li></ul>Work Location: In person

Pavago

Job Title: Data Engineer
 Position Type: Full-Time, Remote
 Working Hours: U.S. client business hours (with flexibility for pipeline monitoring and data refresh cycles)
 
About the Role: 
Our client is seeking a Data Engineer to design, build, and maintain reliable data pipelines and infrastructure that deliver clean, accessible, and actionable data. This role requires strong software engineering fundamentals, experience with modern data stacks, and an eye for quality and scalability. The Data Engineer ensures data flows seamlessly from source systems to warehouses and BI tools, powering decision-making across the business.
 
Responsibilities:Pipeline Development: 
<ul>
<li>Build and maintain ETL/ELT pipelines using Python, SQL, or Scala.</li>
<li>Orchestrate workflows with Airflow, Prefect, Dagster, or Luigi.</li>
<li>Ingest structured and unstructured data from APIs, SaaS platforms, relational databases, and streaming sources.</li>
</ul>
Data Warehousing: 
<ul>
<li>Manage data warehouses (Snowflake, BigQuery, Redshift).</li>
<li>Design schemas (star/snowflake) optimized for analytics.</li>
<li>Implement partitioning, clustering, and query performance tuning.</li>
</ul>
Data Quality & Governance: 
<ul>
<li>Implement validation checks, anomaly detection, and logging for data integrity.</li>
<li>Enforce naming conventions, lineage tracking, and documentation (dbt, Great Expectations).</li>
<li>Maintain compliance with GDPR, HIPAA, or industry-specific regulations.</li>
</ul>
Streaming & Real-Time Data: 
<ul>
<li>Develop and monitor streaming pipelines with Kafka, Kinesis, or Pub/Sub.</li>
<li>Ensure low-latency ingestion for time-sensitive use cases.</li>
</ul>
Collaboration: 
<ul>
<li>Partner with analysts and data scientists to provide curated, reliable datasets.</li>
<li>Support BI teams in building dashboards (Tableau, Looker, Power BI).</li>
<li>Document data models and pipelines for knowledge transfer.</li>
</ul>
Infrastructure & DevOps: 
<ul>
<li>Containerize data services with Docker and orchestrate in Kubernetes.</li>
<li>Automate deployments via CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI).</li>
<li>Manage cloud infrastructure using Terraform or CloudFormation.</li>
</ul>
What Makes You a Perfect Fit: 
<ul>
<li>Passion for clean, reliable, and scalable data.</li>
<li>Strong problem-solving skills with debugging mindset.</li>
<li>Balance of software engineering rigor and data intuition.</li>
<li>Collaborative communicator who thrives in cross-functional environments.</li>
</ul>
Required Experience & Skills (Minimum): 
<ul>
<li>3+ years in data engineering or back-end development.</li>
<li>Strong Python and SQL skills.</li>
<li>Experience with at least one major data warehouse (Snowflake, Redshift, BigQuery).</li>
<li>Familiarity with pipeline orchestration tools (Airflow, Prefect).</li>
</ul>
Ideal Experience & Skills: 
<ul>
<li>Experience with dbt for transformations and data modeling.</li>
<li>Streaming data experience (Kafka, Kinesis, Pub/Sub).</li>
<li>Cloud-native data platforms (AWS Glue, GCP Dataflow, Azure Data Factory).</li>
<li>Background in regulated industries (healthcare, finance) with strict compliance.</li>
</ul>
What Does a Typical Day Look Like?
 A Data Engineer’s day revolves around keeping pipelines running, improving reliability, and enabling teams with high-quality data. You will:
 <ul>
<li>Check pipeline health in Airflow/Prefect and resolve any failed jobs.</li>
<li>Ingest new data sources, writing connectors for APIs or SaaS platforms.</li>
<li>Optimize SQL queries and warehouse performance to reduce costs and latency.</li>
<li>Collaborate with analysts/data scientists to deliver clean datasets for dashboards and models.</li>
<li>Implement validation checks to prevent downstream reporting issues.</li>
<li>Document and monitor pipelines so they’re reproducible, scalable, and audit-ready.</li>
</ul>
In essence: you ensure the business has accurate, timely, and trustworthy data powering every decision.
 
Key Metrics for Success (KPIs): 
<ul>
<li>Pipeline uptime ≥ 99%.</li>
<li>Data freshness within agreed SLAs (hourly, daily, weekly).</li>
<li>Zero critical data quality errors reaching BI/analytics.</li>
<li>Cost-optimized queries and warehouse performance.</li>
<li>Positive feedback from data consumers (analysts, scientists, leadership).</li>
</ul>
Interview Process: 
<ul>
<li>Initial Phone Screen</li>
<li>Video Interview with Pavago Recruiter</li>
<li>Technical Task (e.g., build a small ETL pipeline or optimize a SQL query)</li>
<li>Client Interview with Engineering/Data Team</li>
<li>Offer & Background Verification</li>
</ul>

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4103 data engineer jobs IN Pakistan

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