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cloud data engineer

Godai Tech

About GodaitecAt Godaitec, we are a full-service technology thought partner dedicated to empowering innovation. We blend creativity, strategy, and technology to transform ideas into scalable, future-ready solutions. From Software Development and Solution Consulting to cutting-edge Data Analytics and Emerging Technologies (AI, IoT, Blockchain), we help businesses turn their data into strategic value.We are looking for a passionate Data Engineer to join our growing team. If you are driven by building robust data ecosystems and have a knack for solving complex data challenges, we want to hear from you.Role OverviewWe are seeking a skilled Data Engineer with up to 2 years of hands-on experience to build, optimize, and maintain our data infrastructure. You will play a critical role in our Data Analytics vertical, working on high-impact projects involving ETL pipelines, cloud data warehousing, and data governance. You will bridge the gap between raw data and actionable insights, ensuring our clients can make smarter, faster decisions.Key Responsibilities<ul><li>Pipeline Development: Design, build, and maintain scalable ETL/ELT pipelines using industry-standard tools (Informatica, Talend, Spark) to ingest data from various sources.</li><li>Data Modeling &amp; Architecture: Develop robust data models and architectures that support business intelligence and advanced analytics requirements.</li><li>Cloud Data Engineering: Implement and manage data solutions on cloud platforms (Databricks, Azure, AWS, or GCP).</li><li>Data Quality &amp; Governance: Establish frameworks for data quality, reliability, and governance to ensure data accuracy and compliance across the organization.</li><li>Orchestration &amp; Automation: Schedule and monitor workflows using orchestration tools like Airflow or Prefect to ensure timely data delivery.</li><li>Containerization &amp; CI/CD: Utilize Docker and Kubernetes for containerization and Jenkins for CI/CD pipelines to streamline deployment processes.</li><li>Collaboration: Work closely with Data Scientists and Analysts to prepare data for visualization and machine learning models.</li></ul>Candidate Profile &amp; Requirements1. Education &amp; Experience<ul><li>Bachelor&rsquo;s degree in computer science, Mathematics and statistics, or a related field.</li><li>Up to 2 years of proven hands-on experience in data engineering.</li><li>I must have prior experience working on Data Modeling, Data Operations, ETL pipelines, Data Quality, and Governance related projects.</li></ul>2. Technical Proficiency<ul><li>ETL &amp; Big Data: Strong proficiency in tools like Informatica or Talend. Experience with Big Data technologies such as Hadoop, Spark, and Kafka.</li><li>Languages &amp; Frameworks: Expert-level SQL and Python skills. Experience with Linux environments and PySpark for large-scale data processing.</li><li>Cloud Platforms: Hands-on experience with Databricks and major cloud providers (Azure, AWS, or GCP).</li><li>Orchestration: Proficiency in workflow management using Apache Airflow or Prefect.</li><li>Containerization &amp; CI/CD: Familiarity with Jenkins, Docker, and Kubernetes for deploying and scaling applications.</li><li>Data Visualization: Ability to integrate data with visualization tools like Tableau or Power BI, and Python libraries like Matplotlib or Seaborn.</li></ul>3. &quot;Good to Have&quot; (Bonus Skills)<ul><li>Generative AI &amp; Agentic AI: Knowledge of or interest in GenAI applications and Agentic AI workflows is a significant plus as we expand into emerging technologies.</li><li>Certifications: Any active Data Engineering certification from GCP, AWS, or Azure will be considered a strong advantage.</li></ul>Why Join Godaitec?<ul><li>Work on Emerging Tech: Get the chance to work not just on traditional data stacks but also explore AI, IoT, and Blockchain integrations.</li><li>Growth &amp; Learning: We are a learning-centric organization that supports your professional development through exposure to diverse industries (Finance, Healthcare, Retail, etc.).</li><li>Impact: Your work will directly influence the strategic decisions of global clients.</li></ul>Job Type: Full-timeEducation:<ul><li>Bachelor's (Preferred)</li></ul>Location:<ul><li>Karachi (Preferred)</li></ul>Work Location: In person

Data Engineer (Mid-Level)

Squarera

We are looking for a motivated Snowflake Developer with 1&ndash;3 years of experience in data engineering and cloud-based data warehousing. The ideal candidate should have strong SQL skills, hands-on experience with Snowflake features, and a solid understanding of modern ETL/ELT processes.You will be responsible for building and optimizing scalable data pipelines, ensuring high data quality, and supporting analytics and reporting requirements across teams.Key Responsibilities:<ul><li>Develop, implement, and maintain data warehouse solutions using the Snowflake Cloud Data Platform.</li><li>Build and optimize ETL/ELT pipelines using tools such as dbt, Airflow, or Azure Data Factory.</li><li>Design and maintain data models, schemas, and transformations for analytics and reporting.</li><li>Implement data performance optimization, partitioning, and clustering strategies in Snowflake.</li><li>Manage data access, roles, and security policies.</li><li>Integrate Snowflake with cloud storage and BI tools like Power BI, Tableau, or Looker.</li><li>Troubleshoot and resolve issues in data ingestion, transformation, and performance.</li></ul>Required Skills &amp; Experience:<ul><li>1&ndash;3 years of experience as a Snowflake Developer or Data Engineer.</li><li>Strong command over SQL and data modeling concepts (star/snowflake schema).</li><li>Practical experience with Snowflake architecture (warehouses, Snowpipes, Streams, Tasks, etc.).</li><li>Familiarity with cloud environments (AWS, Azure, or GCP).</li><li>Experience working with structured and semi-structured data (JSON, Parquet, etc.).</li><li>Basic knowledge of Python for scripting and data manipulation.</li><li>Good understanding of ETL/ELT workflows and best practices.</li></ul>Preferred Qualifications:<ul><li>SnowPro Core Certification (a plus).</li><li>Experience in CI/CD pipelines and version control (Git, Jenkins).</li><li>Exposure to data governance and security compliance processes.</li></ul>Benefits:<ul><li>Market-competitive salary</li><li>Opportunity for international travel</li><li>Medical coverage</li><li>Annual performance-based bonus</li><li>Collaborative and innovative work environment</li></ul>Job Type: Full-timeWork Location: In person

Snowflake Developer

HR Ways

Client C&#65279;ompany Introduction: &#65279;*It is a leading &#65279;&#65279;*software engineering company delivering innovative, AI-powered platforms for global clients.&#65279;Opening: Data Engineer (AWS Integration)Key Responsibilities:Data Lake Architecture: -Design, implement, and maintain a data lake on AWS using Iceberg tables on S3, ensuring data consistency, high availability, and easy querying. &#65279; &#65279;-Work with AWS Glue for ETL processes, creating Glue jobs to process, transform, and load data from SQL Server and other sources into Iceberg tables. &#65279;&#65279;-Implement and optimize Spark-based data transformations in AWS Glue, ensuring efficient and scalable data workflows.&#65279; &#65279; &#65279;SQL Server to AWS Migration: &#65279;-Lead the migration of on-premises SQL Server data to AWS S3 using AWS Glue, DMS, and other relevant tools. &#65279;-Design and implement CDC (Change Data Capture) pipelines to enable real-time data replication from SQL Server to AWS services like S3, Iceberg, and Redshift. &#65279; &#65279;Data Integration &amp; Management: &#65279;-Design and implement data pipelines for batch and real-time data processing, leveraging AWS DMS, Kinesis, and Glue Streaming. &#65279;-Automate data loading, transformation, and archiving processes with Glue and ensure the correct data schema management and data governance. &#65279;-Set up and maintain data cataloging systems using AWS Glue Data Catalog to organize and manage metadata for Iceberg tables. &#65279; &#65279;Querying with Athena: &#65279;-Use AWS Athena for querying Iceberg tables on S3, enabling high-performance, low-latency SQL querying on large datasets stored in Iceberg format. &#65279;-Optimize Athena queries to improve performance and manage large-scale data sets effectively. &#65279;-Design efficient partitioning strategies and manage the Iceberg tables using Athena's native support for Iceberg. &#65279; &#65279;Continuous Improvement &amp; Optimization: &#65279;-Implement data compaction strategies to reduce small file issues in Iceberg and optimize storage and query performance. &#65279;-Continuously monitor, troubleshoot, and optimize data pipelines for performance, cost efficiency, and data quality. &#65279; &#65279;Collaboration &amp; Documentation: &#65279;-Work closely with data scientists, analysts, and business teams to understand data needs and develop solutions that support their goals. &#65279;-Provide clear documentation on architecture, solutions, and workflows to ensure smooth knowledge transfer and maintainability. &#65279; &#65279;Required Skills &amp; Qualifications: &#65279;Experience: &#65279;-Proven experience (3+ years) in data engineering roles with expertise in SQL Server, AWS services, and Iceberg. &#65279;-Hands-on experience with AWS Glue, AWS DMS, S3, and Kinesis in building scalable and reliable data pipelines. -Solid understanding of Change Data Capture (CDC) and its implementation with SQL Server and AWS DMS. &#65279;-Experience with Apache Iceberg for building data lakes and managing large-scale, versioned data on S3. &#65279;-Strong knowledge of ETL processes, data modeling, and data transformation using Spark and Glue. &#65279;-AWS Athena experience for querying and managing Iceberg tables in S3. &#65279; &#65279; Technical Skills: &#65279;-SQL Server: Expertise in database administration, SQL queries, stored procedures, and performance tuning. &#65279;-AWS Glue: Experience in creating, debugging, and deploying Glue jobs and managing Glue Data Catalog. &#65279;-AWS DMS: Experience with migrating and replicating data from SQL Server to AWS cloud services, including CDC. &#65279;-Apache Iceberg: Practical knowledge of Iceberg table formats, partitioning, compaction, and schema evolution. &#65279;-AWS S3: Experience managing large datasets in S3, implementing partitioning strategies, and optimizing storage. &#65279;-Kinesis: Familiarity with real-time streaming data pipelines using Kinesis Data Streams and Glue Streaming. &#65279;-AWS Athena: Strong experience querying Iceberg tables and optimizing large-scale data queries. &#65279; &#65279; Tools &amp; Technologies: &#65279;-Apache Spark (for Glue and standalone Spark jobs) &#65279;-SQL, Python, AWS SDK for automation, and scripting tasks. &#65279;-Data governance: Experience with AWS Lake Formation for security and access management in a data lake environment. &#65279; &#65279;Desired Soft Skills: &#65279;-Strong problem-solving skills with the ability to troubleshoot complex data issues. &#65279;-Ability to collaborate effectively with cross-functional teams (data scientists, analysts, DevOps, and stakeholders). &#65279;-Strong communication skills to document and explain technical concepts clearly to both technical and non-technical audiences. &#65279;-Detail-oriented with a focus on data quality, integrity, and performance.&#65279;Experience: 3 + years &#65279;Work Timings: (Monday to Fri:11:00 AM - 7:30 PM)&#65279; &#65279;Work Mode: (Hybrid - Karachi, Pakistan) &amp; (Hybrid - Kolkata and Ahmadabad, India) &#65279;Salary: Tax-free (USD)&#65279;&#65279;&#65279;&#65279;About HR Ways: HR Ways is an award-winning Technical Recruitment Firm helping software houses and IT Product companies internationally and locally to find IT Talent. HR Ways is engaged by 300+ Employers worldwide ranging from the world's biggest SaaS Companies to the most competitive Startups. We have entities in Dubai, Canada, the US, the UK, Pakistan, India, Saudi Arabia, Portugal, Brazil, and other parts of the world. Join our Whatsapp Channel https://shorturl.at/983az to stay updated or visit www.hrways.co to know more.Job Type: Full-timeWork Location: In person

Data Engineer

MonetizeMore

<div><h3 class="jobSectionHeader">About MonetizeMore</h3>
MonetizeMore is a global leader in ad tech, helping publishers maximize their ad revenue through advanced optimization, data, and automation. Our fully remote team is distributed across the world, driven by innovation, autonomy, and measurable impact.<h3 class="jobSectionHeader">
Role Overview</h3>
We are looking for a Data Infrastructure Engineer to design, build, and maintain scalable data systems that support analytics, machine learning, and business intelligence at MonetizeMore. You will collaborate closely with data engineers, analysts, and product teams to ensure our data pipelines are reliable, efficient, and secure.
In addition to core data infrastructure responsibilities, you will occasionally work on Airflow DAGs and orchestration tasks, supporting our data workflow automation initiatives.<h3 class="jobSectionHeader">
Key Responsibilities</h3><ul><li>
Design, implement, and maintain scalable, high-performance data infrastructure.</li><li>
Manage the data pipelines using Apache Airflow for orchestration and scheduling.</li><li>
Develop and deploy data services and tools using Kubernetes and containerized environments.</li><li>
Leverage AWS services (e.g., S3, Lambda, Athena, ECS/EKS, Glue) for data storage, processing, and orchestration.</li><li>
Ensure reliability, performance, and cost efficiency of data systems.</li><li>
Collaborate with cross-functional teams to support data-driven initiatives and ad tech systems.</li><li>
Implement monitoring, logging, and alerting for all critical data infrastructure components.</li><li>
Champion best practices in data security, governance, and DevOps for data workflows.</li></ul><h3 class="jobSectionHeader">
Qualifications</h3>
Required:<ul><li>
1-2 years of experience in data infrastructure roles.</li><li>
Strong proficiency with Python and SQL.</li><li>
Solid understanding of AWS data and compute services (S3, Athena, ECS/EKS, etc.).</li><li>
Experience in CI/CD, infrastructure-as-code (Terraform, CloudFormation, or similar).</li><li>
Experience with containerization (Docker).</li><li>
Strong problem-solving and debugging skills.</li><li>
Experience with transactional database maintenance. Preferred: Postgres</li></ul>
Preferred:<ul><li>
Knowledge of data warehousing tools like Athena, or BigQuery.</li><li>
Experience managing workflows with Apache Airflow.</li><li>
Hands-on experience deploying and maintaining workloads on Kubernetes.</li><li>
Familiarity with real-time data streaming (Kafka, Kinesis, etc.).</li><li>
Exposure to monitoring and observability tools (Prometheus, Grafana, ELK Stack).</li></ul><h3 class="jobSectionHeader">
Why MonetizeMore</h3><ul><li>
100% remote, flexible work environment.</li><li>
Work with cutting-edge ad tech and data systems.</li><li>
Collaborative, globally distributed team.</li><li>
Opportunities for growth and ownership.</li></ul>
JqWm3YdfU4</div>

Data Infrastructure Engineer

<div>
 
 About MonetizeMore
 
 
 
 MonetizeMore is a global leader in ad tech, helping publishers maximize their ad revenue through advanced optimization, data, and automation. Our fully remote team is distributed across the world, driven by innovation, autonomy, and measurable impact.
 
 
 Role Overview
 
 
 We are looking for a Data Infrastructure Engineer to design, build, and maintain scalable data systems that support analytics, machine learning, and business intelligence at MonetizeMore. You will collaborate closely with data engineers, analysts, and product teams to ensure our data pipelines are reliable, efficient, and secure.
 
 
 In addition to core data infrastructure responsibilities, you will occasionally work on Airflow DAGs and orchestration tasks, supporting our data workflow automation initiatives.
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design, implement, and maintain scalable, high-performance data infrastructure
 </li>
 <li>
 Manage the data pipelines using Apache Airflow for orchestration and scheduling
 </li>
 <li>
 Develop and deploy data services and tools using Kubernetes and containerized environments
 </li>
 <li>
 Leverage AWS services (e.g., S3, Lambda, Athena, ECS/EKS, Glue) for data storage, processing, and orchestration
 </li>
 <li>
 Ensure reliability, performance, and cost efficiency of data systems
 </li>
 <li>
 Collaborate with cross-functional teams to support data-driven initiatives and ad tech systems
 </li>
 <li>
 Implement monitoring, logging, and alerting for all critical data infrastructure components
 </li>
 <li>
 Champion best practices in data security, governance, and DevOps for data workflows
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 Required:
 
 
 <ul>
 <li>
 1-2 years of experience in data infrastructure roles
 </li>
 <li>
 Strong proficiency with Python and SQL
 </li>
 <li>
 Solid understanding of AWS data and compute services (S3, Athena, ECS/EKS, etc.)
 </li>
 <li>
 Experience in CI/CD, infrastructure-as-code (Terraform, CloudFormation, or similar)
 </li>
 <li>
 Experience with containerization (Docker)
 </li>
 <li>
 Strong problem-solving and debugging skills
 </li>
 <li>
 Experience with transactional database maintenance. Preferred: Postgres
 
 
 </li>
 </ul>
 Preferred:
 
 
 <ul>
 <li>
 Knowledge of data warehousing tools like Athena, or BigQuery
 </li>
 <li>
 Experience managing workflows with Apache Airflow
 </li>
 <li>
 Hands-on experience deploying and maintaining workloads on Kubernetes
 </li>
 <li>
 Familiarity with real-time data streaming (Kafka, Kinesis, etc.)
 </li>
 <li>
 Exposure to monitoring and observability tools (Prometheus, Grafana, ELK Stack)
 
 
 </li>
 </ul>
 Why MonetizeMore
 
 
 <ul>
 <li>
 100% remote, flexible work environment
 </li>
 <li>
 Work with cutting-edge ad tech and data systems
 </li>
 <li>
 Collaborative, globally distributed team
 </li>
 <li>
 Opportunities for growth and ownership
 
 
 </li>
 </ul>
 Powered by JazzHR
 
 
 JqWm3YdfU4
</div>

Datamatics Global Services Ltd

<div>Position: iOS Developer / Engineer 
Contract Type: Short-Term DMT Contract (3&ndash;6 Months) 
Location: Offshore 
Experience Level: Mid&ndash;Senior (5-7 Years)<h2 class="jobSectionHeader"> 
Role Overview</h2>
We are looking for an experienced iOS Developer / Engineer to design, build, and maintain high-quality mobile applications for iPhone and iPad. The ideal candidate should be proficient in Swift 6, modern concurrency, SwiftUI, and advanced iOS frameworks to deliver seamless, user-friendly applications.<h2 class="jobSectionHeader"> 
Key Responsibilities</h2><ul><li>
Design and develop iOS applications using Swift 6 with structured concurrency.</li><li>
Build responsive interfaces using SwiftUI (with UIKit as secondary knowledge).</li><li>
Implement efficient data management using SwiftData.</li><li>
Develop modular and scalable application architecture using The Composable Architecture (TCA).</li><li>
Create interactive features like Live Activities and Dynamic Island integrations.</li><li>
Implement App Intents &amp; Shortcuts for enhanced user automation support.</li><li>
Work with Xcode Cloud and Fastlane for CI/CD automation.</li><li>
Collaborate with designers, QA, and backend teams to ensure end-to-end delivery.</li></ul><h2 class="jobSectionHeader"> 
Key Expertise Required</h2><ul><li>
Swift 6 + structured concurrency</li><li>
SwiftUI (UIKit secondary skill)</li><li>
SwiftData (Core Data replacement)</li><li>
The Composable Architecture (TCA)</li><li>
Live Activities &amp; Dynamic Island</li><li>
App Intents &amp; Shortcuts integration</li><li>
Xcode Cloud + Fastlane automation</li></ul><h2 class="jobSectionHeader"> 
Preferred Skills</h2><ul><li>
Experience publishing apps to the App Store</li><li>
Strong debugging and performance optimization skills</li><li>
Familiarity with REST APIs, JSON, and modern iOS design patterns</li></ul>
EooCDVnDAg</div>

iOS Developer

<div>Job Title: Lead Confluent Kafka Engineer/Architect 
Location: Remote (Pak) / Hybrid (Riyadh, KSA) 
Employment Type: Full-Time / Contract-to-Hire 
Experience Level: 10+ years (Senior/Lead) 
 
Role Summary 
As a Lead Confluent Kafka Engineer, you'll architect, design, setup, install, implement and optimize high-throughput data streaming solutions using Confluent Platform and Apache Kafka. You'll lead a team of engineers in delivering production-grade pipelines, ensuring scalability, reliability, and security. This role involves hands-on development, mentoring, and collaborating with data architects, DevOps, and stakeholders to implement event-driven architectures. You'll champion best practices in real-time data processing, from proof-of-concepts to enterprise deployments, including full lifecycle management from installation to optimization. 
 
Key Responsibilities<ul><li>
Architecture &amp; Design: Lead the design of scalable Kafka clusters and Confluent-based ecosystems (e.g., Kafka Streams, ksqlDB, Schema Registry, Connect) for on-prem, hybrid, and multi-cloud (GCP) environments.</li><li>
Implementation &amp; Development: Build and maintain real-time data pipelines, integrations, and microservices using Kafka producers/consumers; integrate with tools like Flink, Spark, or ML frameworks for advanced analytics.</li><li>
Installation &amp; Setup: Oversee the end-to-end installation and initial configuration of Confluent Platform and Apache Kafka clusters, including:<ul><li>
Deploying Confluent Enterprise/Community editions on Kubernetes (via Helm/Operator), bare-metal servers, or managed cloud services (e.g., Confluent Cloud, GCP).</li><li>
Configuring brokers, ZooKeeper/KRaft mode, topics, partitions, replication factors, and security settings (e.g., SSL/TLS, SASL, ACLs) using Ansible, Terraform, or Confluent CLI.</li><li>
Setting up auxiliary components like Schema Registry, Kafka Connect clusters, and monitoring agents (e.g., JMX exporters) with automated scripts for reproducible environments.</li><li>
Performing initial health checks, load testing (e.g., with Kafka's performance tools), and integration with existing infrastructure (e.g., VPC peering, load balancers).</li></ul></li><li>
Operations &amp; Maintenance: Oversee monitoring, troubleshooting, performance tuning, and lifecycle management (upgrades, patching) of Kafka/Confluent instances; implement DevSecOps practices for CI/CD pipelines.</li><li>
Team Leadership: Mentor junior engineers, conduct code reviews, and drive technical proofs-of-concept (POCs); gather requirements and define standards for Kafka as a managed service (e.g., access controls, documentation).</li><li>
Optimization &amp; Innovation: Ensure high availability (&gt;99.99%), fault tolerance, and cost-efficiency; explore emerging features like Kafka Tiered Storage or Confluent Cloud integrations for AI workloads.</li><li>
Collaboration &amp; Delivery: Partner with cross-functional teams (data engineers, architects, product owners) to align streaming solutions with business goals; provide thought leadership on event-driven patterns.</li><li>
Security &amp; Compliance: Implement RBAC, encryption, and auditing; conduct root-cause analysis for incidents and ensure GDPR/HIPAA compliance in data flows.</li></ul>
Required Qualifications &amp; Skills<ul><li>
Bachelor's/Master's in Computer Science, Engineering, or related; certifications like Confluent Developer/Administrator a plus.</li><li>
10+ years in software engineering; 5+ years hands-on with Apache Kafka &amp; Confluent Platform (Cloud/Enterprise editions).</li><li>
Proficiency in Java/Scala/Python (8/11+); Kafka Streams/Connect/ksqlDB; Schema Registry; REST/gRPC APIs.</li><li>
Event-driven/microservices design; data pipeline optimization; handling high-volume streams (TB/day scale).</li><li>
Expertise in containerization (Docker/Kubernetes); CI/CD (Jenkins/GitHub Actions); Terraform/Ansible for IaC.</li><li>
Multi-cloud experience (AWS, GCP, Azure); monitoring tools (Prometheus, Grafana, Confluent Control Center).</li><li>
Experience with streaming integrations (e.g., Flink, Spark Streaming for CDC).
</li><li>Contributions to open-source Kafka projects or publications on streaming architectures.
</li><li>Knowledge of AI/ML data pipelines (e.g., Kafka + TensorFlow/PyTorch).
</li><li>Familiarity with observability tools and security (OAuth, Kerberos).
</li><li>Strong problem-solving, communication, and leadership; experience leading POCs and cross-team projects.</li><li>
Agile/Scrum leadership in fast-paced environments.</li><li>
Experience in client facing roles and leading teams.</li></ul>
eSAVL5n77F</div>

Lead Confluent Kafka Engineer / Architect

Explore 1020+ Cloud data engineer in Karachi this December. Find roles across top companies and apply now to boost your career.

1020 cloud data engineer jobs IN Karachi

Data Engineer (Mid-Level)

Snowflake Developer

Data Engineer

Data Infrastructure Engineer

Data Infrastructure Engineer

iOS Developer

Lead Confluent Kafka Engineer / Architect