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cloud data engineer

Cloudelligent

<div>Position Title: AWS Data Engineer 
Job Timings: 8:00 AM &ndash; 5:00 PM CST (6:00 PM- 3:00 AM PKT) 
Location: Lahore 
 
About Cloudelligent 
 
Cloudelligent is Cloud-native consultancy and AWS Advanced consulting partner! We specialize in providing bespoke cloud solutions to Startups &amp; SMBs. Being a next-gen cloud service provider, Cloudelligent helps businesses to make the most out of their cloud investment. We have an international footprint with a diverse team of domain experts, and we are customer obsessed. 
 
Job Objective 
 
We are seeking an experienced Data Engineer with a strong background in data engineering, database optimization, and cloud-based data solutions, particularly on AWS. The ideal candidate will have hands-on experience with both SQL and NoSQL databases and be proficient in migrating, managing, and modernizing data platforms. You should be skilled in designing and maintaining scalable, secure, and high-performance data infrastructure in the cloud. 
 
Responsibilities<ul><li>
Design, implement, and manage cloud-based data infrastructure using Amazon RDS, Aurora, and EC2-hosted databases.</li><li>
Administer and optimize PostgreSQL, MySQL, and Oracle databases, ensuring high availability, performance, and cost-efficiency.</li><li>
Perform data migrations and transformations using AWS Database Migration Service (DMS) and other tools.</li><li>
Collaborate with data architects, engineers, and DevOps teams to deliver reliable and scalable data solutions.</li><li>
Support developers by analyzing and optimizing SQL queries and data workflows for performance and efficiency.</li><li>
Monitor and troubleshoot data issues, ensuring availability, security, and compliance.</li><li>
Implement data automation, infrastructure as code (IaC), and CI/CD pipelines for database and data pipeline deployments.</li><li>
Ensure data security, encryption, and compliance with industry best practices and internal policies.</li><li>
Maintain comprehensive documentation on data architecture, processes, and procedures.</li><li>
Stay up to date with emerging AWS features, data engineering tools, and industry best practices.</li></ul> 

Requirements<ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Information Technology, or a related field.</li><li>
4+ years of experience in data engineering or database engineering, including hands-on experience with databases on AWS.</li><li>
Strong experience with AWS data services such as RDS, Aurora, and DMS.</li><li>
Proficient in performance tuning, indexing strategies, partitioning, and query optimization.</li><li>
Strong scripting and automation experience using Python, Bash, or similar tools.</li><li>
Experience with infrastructure as code tools like Terraform or CloudFormation.</li><li>
Solid understanding of backup strategies, monitoring tools, and security best practices.</li><li>
Familiarity with multi-account AWS environments and cross-region replication.</li><li>
Excellent communication and problem-solving skills.</li></ul> 

Highly Desirable<ul><li>
AWS Certification (e.g., AWS Certified Data Engineer &ndash; Associate, AWS Certified Solutions Architect &ndash; Associate).</li><li>
Experience with large-scale on-prem to AWS data migrations.</li><li>
Familiarity with data governance, compliance, and auditing tools.</li><li>
Exposure to data lake architecture and AWS services like Glue, Athena, or Kinesis is a plus.</li></ul>
AKibWGHF17</div>

AWS Data Engineer

H2o Labs

Data EngineerTiming: 05:00 PM to 02:00 AMJob Type: Full-Time (On-site)Location: Johar TownAbout the Role We are looking for a highly skilled and versatile Data Engineer to join our team. The ideal candidate will have expertise in building and maintaining scalable data infrastructure, focusing on data pipelines, cloud technologies, and data processing systems. This role requires hands-on experience in designing and deploying reliable, high-performance data solutions that meet the demands of large-scale operations. Key Responsibilities:<ul><li>Data Infrastructure &amp; Pipeline Development:</li><li>Design, build, and maintain efficient, scalable, and robust data pipelines for data extraction, transformation, and loading (ETL).</li><li>Develop and optimize SQL queries for complex data processing and ensure high data quality.</li><li>Implement and manage automated data workflows using orchestration tools like Airflow.</li><li>Cloud Data Platforms:</li><li>Work extensively with cloud-based platforms like AWS, Azure, or GCP to build and manage data infrastructure.</li><li>Utilize services such as Azure Data Factory, AWS Glue, BigQuery, or similar tools for data ingestion, transformation, and storage.</li><li>Implement monitoring, logging, and alerting to ensure continuous data pipeline performance and reliability.</li><li>Data Modeling &amp; Warehousing:</li><li>Design and implement dimensional models and maintain data warehouses to support business intelligence and analytics.</li><li>Develop and manage data schemas, ensuring consistency and integrity across systems.</li><li>Optimize data storage, querying, and retrieval processes to meet business needs.</li><li>Data Processing &amp; Stream Handling:</li><li>Build real-time data pipelines using tools like Apache Kafka, Spark, or similar technologies for data stream processing.</li><li>Handle large datasets and complex transformations to support analytical workflows and reporting.</li></ul>Key Skills &amp; Qualifications:<ul><li>Bachelor's degree in Computer Science, Data Engineering, or a related field (or equivalent experience).</li><li>Proficiency in SQL, with hands-on experience in complex queries, joins, and optimizations.</li><li>Strong experience with cloud platforms (AWS, Azure, GCP), with tools like Azure Data Factory, AWS Glue, BigQuery, or similar.</li><li>Expertise in building and maintaining scalable ETL pipelines using tools like Airflow, DBT, or Spark.</li><li>Experience with data modeling and warehousing, including dimensional modeling, schema design, and data integrity management.</li><li>Familiarity with stream processing technologies like Kafka and Spark.</li><li>Hands-on experience with containerization tools like Docker and orchestration platforms like Kubernetes.</li><li>Strong problem-solving skills and the ability to troubleshoot and optimize complex data workflows.</li><li>Experience with data security, governance, and compliance standards.</li><li>Strong communication skills to collaborate effectively with technical and non-technical teams.</li></ul>Preferred Skills:<ul><li>Experience with data visualization tools (e.g., Power BI, Tableau) for creating dashboards and reporting.</li><li>Familiarity with Python for data transformations, automation, and scripting.</li><li>Experience with metadata management and data cataloguing tools.</li><li>Familiarity with monitoring tools like Datadog, Prometheus, or Grafana.</li></ul>Benefits<ul><li>Commissions- On Success fulling closing of project</li><li>Meal Facility &ndash; Enjoy delicious meals at the office.</li><li>Gym Facility &ndash; Stay active with access to our partner gym.</li><li>Health Support &ndash; Get free medical consultations when needed.</li><li>Restaurant Perks &ndash; Enjoy special discounts and offers through our restaurant collaborations.</li></ul>Job Type: Full-timePay: Rs150,000.00 - Rs250,000.00 per monthWork Location: In person

Data Engineer

Taraki

<div>
 Taraki is hiring for one of its clients.
 
 
 Location: Remote
 
 
 Experience Level: 5 to 8 years in Data Engineering, Data Pipelines, and Cloud-based Data Platforms
 
 
 Department: Data &amp; AI Engineering
 
 
 Compensation: PKR 600,000 to 850,000 (based on experience)
 
 
 Role Summary:
 
 
 The Data Engineer will design and build large-scale, high-performance data pipelines to support segmentation, pricing simulation, and offer decisioning. They will ensure efficient data ingestion from telco systems (CDRs, usage, recharge, offer purchase), transformation, and integration with ML models and orchestration modules.
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Design and develop scalable ETL / ELT data pipelines to process 50M+ customer records daily.
 </li>
 <li>
 Ingest data from OCS, CRM, DWH, and Adobe RT-CDP or other customer data platforms.
 </li>
 <li>
 Build and maintain Customer Profile Store and Feature Store for real-time and batch processing.
 </li>
 <li>
 Implement data validation, quality, and lineage frameworks.
 </li>
 <li>
 Optimize query performance and cost efficiency for batch and streaming workloads.
 </li>
 <li>
 Collaborate with Data Scientists to prepare model training datasets and deploy inference pipelines.
 </li>
 <li>
 Integrate outputs with Decision Engine and Real-Time Offer Orchestration Module.
 </li>
 <li>
 Automate pipelines using CI/CD and maintain environment configurations across Dev, UAT, and Prod.
 
 
 
 </li>
 </ul>
 
 Required Skills
 
 
 
 <ul>
 <li>
 Strong in SQL, PySpark, and DataFrame APIs for data transformation.
 </li>
 <li>
 Expertise in Data Modeling (customer-level, event-level, offer-level).
 </li>
 <li>
 Understanding of data partitioning, schema evolution, and performance tuning.
 </li>
 <li>
 Experience in stream processing (Kafka, Spark Streaming, Kinesis).
 </li>
 <li>
 Knowledge of data quality frameworks (e.g., Great Expectations, Deequ).
 </li>
 <li>
 Familiarity with ETL orchestration tools (Airflow, dbt, or Dagster).
 </li>
 <li>
 Ability to work with cloud-native data platforms and object storage.
 
 
 
 </li>
 </ul>
 Tools &amp; Technologies
 
 
 Data Platform: Databricks, AWS Glue, Azure Data Factory, Snowflake, BigQuery
 
 
 Streaming: Kafka, Kinesis, Spark Streaming
 
 
 Storage: S3, Delta Lake, Parquet, Hive
 
 
 Workflow Orchestration: Airflow, dbt, Dagster, Prefect
 
 
 Scripting: Python, SQL, PySpark
 
 
 DevOps: Git, Jenkins, Terraform
 
 
 Monitoring &amp; Validation: Great Expectations, Deequ, DataDog
 
 
 
 Preferred (Nice-to-Have)
 
 
 
 <ul>
 <li>
 Experience with telecom datasets (Recharge, Usage, Balance, Offer Subscription).
 </li>
 <li>
 Knowledge of DecisionRules.io, n8n, or KNIME for orchestration workflows.
 </li>
 <li>
 Familiarity with Adobe AEP data schemas (XDM) or Pricefx integration.
 </li>
 <li>
 Exposure to real-time microservices (REST/GraphQL APIs) for data access.
 
 </li>
 </ul>
</div>

Devsinc

<div>
 Devsinc is seeking a talented
 
 Data Engineer
 
 having minimum of
 
 2 years of professional experience
 
 to join our growing data team. In this role, you will design and build scalable data pipelines, work with modern cloud platforms, and lay the foundation for analytics that drive critical business decisions. From day one, you'll learn from senior engineers, work with a modern cloud stack, and see your contributions make a tangible impact.
 
 
 
 Responsibilities:
 
 
 
 <ul>
 <li>
 Design, develop, and maintain automated ETL/ELT data pipelines for structured and unstructured datasets.
 </li>
 <li>
 Build and optimize scalable, secure, and cost-efficient cloud data solutions using AWS, Azure, or GCP.
 </li>
 <li>
 Model, cleanse, and transform data to support analytics, dashboards, and reporting use-cases.
 </li>
 <li>
 Implement automated testing, monitoring, and alerting to ensure high data quality and reliability.
 </li>
 <li>
 Develop high-performance Python-based services and utilities for data ingestion and processing.
 </li>
 <li>
 Work with APIs, event-driven systems, and streaming platforms for real-time data workflows.
 </li>
 <li>
 Collaborate with cross-functional teams (Data Science, Backend, DevOps, Product) to gather requirements and deliver tailored data solutions.
 </li>
 <li>
 Follow strong software engineering best practices &mdash; clean code, modularity, version control, CI/CD.
 </li>
 <li>
 Document architecture, data flows, schemas, and development standards.
 </li>
 <li>
 Stay updated on evolving data engineering tools, frameworks, and cloud-native technologies
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Software Engineering, or a related field.
 </li>
 <li>
 Minimum 2 years of professional experience
 </li>
 <li>
 Strong knowledge of Python and SQL for data processing and transformation.
 </li>
 <li>
 Hands-on experience with at least one major cloud platform &mdash; AWS, GCP, or Azure.
 </li>
 <li>
 Exposure to cloud-native data services such as AWS Glue, Redshift, Azure Data Factory, BigQuery, Synapse, etc.
 </li>
 <li>
 Familiarity with modern data warehouses &mdash; Snowflake, Redshift, BigQuery, or Synapse.
 </li>
 <li>
 Strong understanding of ETL/ELT frameworks such as dbt, Apache Spark, or Databricks.
 </li>
 <li>
 Experience working with orchestration tools like Apache Airflow, Azure Data Factory Pipelines, or AWS Glue Workflows.
 </li>
 <li>
 Proficiency with version control systems (GitHub, GitLab, Bitbucket) and CI/CD pipelines.
 </li>
 <li>
 Solid understanding of Data Lake architectures (S3, ADLS, GCS) and schema design principles.
 </li>
 <li>
 Basic understanding of data governance, security, compliance, and access management concepts.
 </li>
 <li>
 Familiarity with streaming platforms such as Kafka, Amazon Kinesis, or Google Pub/Sub
 </li>
 <li>
 Collaborative - open to knowledge-sharing and teamwork.
 </li>
 <li>
 Team Player - willing to support peers and contribute to collective success.
 </li>
 <li>
 Growth Minded - eager to learn, improve, and adapt to emerging technologies.
 </li>
 <li>
 Adaptable - flexible in dynamic, fast-paced environments.
 </li>
 <li>
 Customer-Centric - focused on delivering solutions that create real business value
 </li>
 </ul>
</div>

Software 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>
dpdiW5IUw3</div>

Data Infrastructure Engineer

The Services Tree Enterprises 

Job Description: SourceTeK is hiring a Data Engineer for one of our clients based in Johar Town, Lahore. We are looking for a motivated professional with 2&ndash;3+ years of experience in data engineering, especially someone who has hands-on experience with DBT tools and a strong understanding of modern data pipelines.Key Responsibilities:<ul><li>Build, maintain, and optimize data pipelines</li><li>Work with DBT tools for data modeling and transformations</li><li>Collaborate with cross-functional teams to ensure data accuracy and availability</li><li>Troubleshoot and optimize data workflows</li></ul>Requirements:<ul><li>2&ndash;3+ years of experience as a Data Engineer</li><li>Strong experience with DBT tools</li><li>Proficiency in SQL and data pipeline development</li><li>Experience with cloud platforms is a plus</li><li>Strong analytical and problem-solving skills</li></ul>How to Apply: If you&rsquo;re interested, please send your resume to talent@sourcetek.co or apply through Indeed.Job Type: Full-timePay: Rs120,000.00 - Rs200,000.00 per monthExperience:<ul><li>Data Engineer: 2 years (Preferred)</li></ul>Work Location: In person

<div>Position Title: Sr. Data Migration Engineer 
Job Timings: 8am-5pm CST 
Location: Lahore 
 
About Cloudelligent 
Cloudelligent is a Cloud-native consultancy and AWS Advanced consulting partner! We specialize in providing bespoke cloud solutions to the Startups, SMB &amp; enterprise segment. Being a next gen cloud service provider, Cloudelligent helps businesses to make the most out of their cloud investment. We have an international footprint with a diverse team of domain experts, and we are customer- obsessed. 
 
Job Objective 
We&rsquo;re looking for a Senior Data Migration Engineer to drive the data conversion work that powers successful LegalTech SaaS implementations. As firms move from legacy tools to modern platforms, your work ensures that their financial, operational, and practice data is clean, accurate, and ready for day-one use. You&rsquo;ll lead the full ETL lifecycle analyzing legacy structures, mapping data to modern schemas, running test conversions, validating results, and supporting a seamless go-live experience. 
 
Responsibilities<ul><li>
Analyze legacy financial and practice-management data structures and design end-to-end conversion strategies.</li><li>
Collaborate with project managers and implementation consultants to understand mapping requirements and business rules.</li><li>
Translate functional requirements into clear, scalable technical migration plans.</li><li>
Extract data from SQL databases, CSV exports, APIs, and other legacy sources.</li><li>
Write and optimize complex SQL queries (joins, CTEs, validation queries, reconciliation logic).</li><li>
Develop Python scripts or reusable ETL tools to automate recurring processes and improve consistency.</li><li>
Build and maintain detailed data-mapping documentation across all migration objects.</li><li>
Perform dry-run migrations and validate data accuracy across financial and operational modules.</li><li>
Execute final production loads and deliver reconciliation reports for billing, WIP, AR, GL, and related datasets.</li><li>
Investigate and resolve anomalies, data gaps, or logic errors across multiple data sources.</li><li>
Create detailed technical documentation, mapping dictionaries, transformation logic, and conversion specifications.</li><li>
Serve as a primary technical partner to project managers, implementation consultants, and client IT teams.</li><li>
Clearly communicate data issues, risks, and recommendations in both technical and non-technical terms.</li><li>
Help build and enhance migration templates, automation scripts, and best-practice playbooks.</li><li>
Identify opportunities to streamline processes, reduce manual work, and strengthen data quality.</li></ul>
Requirements<ul><li>
4+ years in data migration, ETL engineering, data conversion, or ERP/SaaS system integration.</li><li>
Advanced SQL skills (joins, CTEs, schema work, validation logic, troubleshooting, performance tuning).</li><li>
Strong Excel/Power Query skills and Python experience (Pandas/NumPy a plus).</li><li>
Experience with structured and semi-structured file formats (CSV, JSON, XML).</li><li>
Demonstrated ability to analyze complex datasets, identify patterns, and resolve data-quality issues.</li><li>
Experience executing multi-object migration cycles (dry runs, reconciliations, cutovers).</li><li>
Strong documentation habits and the ability to produce clear technical specifications.</li><li>
Excellent communication skills and comfort working cross-functionally with non-technical stakeholders.</li><li>
Experience in legal-tech, professional services, or financial systems is a plus.</li></ul>
7RvOvrPUPl</div>

Sr. Data Migration Engineer (C4-1125150)

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Sr. Data Migration Engineer (C4-1125150)