cloud engineer

senior data engineer

software engineer

4261- data engineer

ai engineer

data pipeline engineer

Innovaccer

<div>About the Role 
As a Data Engineer at Innovaccer, you will be at the heart of our data infrastructure &mdash; designing, building, and maintaining the scalable pipelines and platforms that power our AI-driven healthcare solutions across the Kingdom of Saudi Arabia. You will play a key role in enabling data-driven decision-making for health systems, payers, and providers, directly contributing to better patient outcomes and operational excellence across the Saudi healthcare landscape.
A Day in the Life<ul><li>
Design, develop, and maintain robust ETL/ELT data pipelines to ingest, transform, and deliver healthcare data from multiple source systems.</li><li>
Build and optimize scalable data models within cloud data warehouses (Snowflake, AWS Redshift, or Azure Synapse) to support analytics and reporting.</li><li>
Collaborate with data scientists, product managers, and clinical informatics teams to understand data needs and translate them into reliable data solutions.</li><li>
Ensure data quality, integrity, and governance by implementing testing frameworks, validation checks, and monitoring alerts across all pipelines.</li><li>
Work with healthcare interoperability standards (HL7, FHIR) to integrate clinical and claims data from diverse health systems in the KSA market.</li><li>
Contribute to infrastructure-as-code practices, supporting CI/CD pipelines and automating deployment of data workflows.</li><li>
Participate in code reviews, architectural discussions, and cross-functional sprint planning to ensure delivery of high-quality, production-grade data products.</li></ul> 
What You Need
Knowledge<ul><li>
Strong understanding of data engineering principles including data modelling, warehousing, and pipeline architecture.</li><li>
Familiarity with healthcare data standards such as HL7, FHIR, ICD-10, and SNOMED CT.</li><li>
Knowledge of cloud platforms (AWS, Azure, or GCP) and their managed data services.</li></ul>
Abilities<ul><li>
Ability to write clean, efficient, and well-documented code in Python and SQL.</li><li>
Ability to independently own and deliver data pipeline projects end-to-end, from requirements gathering to production deployment.</li><li>
Ability to troubleshoot complex data issues and communicate findings clearly to both technical and non-technical stakeholders.</li></ul>
Credentials &amp; Experience<ul><li>
 3&ndash;6 years of hands-on experience in data engineering or a closely related role.</li><li>
Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or a related field.</li><li>
Proven experience with distributed processing frameworks such as Apache Spark or Kafka.</li><li>
Experience with orchestration tools (Apache Airflow, Prefect, or similar) to manage complex workflow dependencies.</li><li>
Prior experience working in healthcare IT or with clinical/claims datasets is strongly preferred.</li></ul>
Preferred Skills<ul><li>
Proficiency in dbt (data build tool) for analytics engineering and data transformation workflows.</li><li>
Experience with real-time streaming pipelines using Apache Kafka or AWS Kinesis.</li><li>
Familiarity with data observability and monitoring tools such as Monte Carlo, Great Expectations, or similar.</li><li>
Understanding of HIPAA, PDPL (Saudi Personal Data Protection Law), and data privacy best practices in a healthcare context.</li><li>
Experience working in an Agile/Scrum environment with cross-functional global teams.</li><li>
Knowledge of Arabic language is a plus for stakeholder communication within the KSA market.</li></ul>
We offer competitive benefits to set you up for success in and outside of work. 
Here&rsquo;s What We Offer<ul><li>
Generous Leaves: Enjoy generous leave benefits of up to 40 days.</li><li>
Parental Leave: Leverage one of industry's best parental leave policies to spend time with your new addition.</li><li>
Health Insurance: We offer comprehensive health insurance to support you and your family, covering medical expenses related to illness, disease, or injury. Extending support to the family members who matter most.</li><li>
Care Program: Whether it&rsquo;s a celebration or a time of need, we&rsquo;ve got you covered with care vouchers to mark major life events. Through our Care Vouchers program, employees receive thoughtful gestures for significant personal milestones and moments of need.</li><li>
Financial Assistance: Life happens, and when it does, we&rsquo;re here to help. Our financial assistance policy offers support through salary advances and personal loans for genuine personal needs, ensuring help is there when you need it most.</li></ul>
Innovaccer is an equal-opportunity employer. We celebrate diversity, and we are committed to fostering an inclusive and diverse workplace where all employees, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, marital status, or veteran status, feel valued and empowered.
Disclaimer:
Innovaccer does not charge fees or require payment from individuals or agencies for securing employment with us. We do not guarantee job spots or engage in any financial transactions related to employment. If you encounter any posts or requests asking for payment or personal information, we strongly advise you to report them immediately to our HR department at px@innovaccer.com. Additionally, please exercise caution and verify the authenticity of any requests before disclosing personal and confidential information, including bank account details. 
About Innovaccer
Innovaccer activates the flow of healthcare data, empowering providers, payers, and government organizations to deliver intelligent and connected experiences that advance health outcomes. The Healthcare Intelligence Cloud equips every stakeholder in the patient journey to turn fragmented data into proactive, coordinated actions that elevate the quality of care and drive operational performance. Leading healthcare organizations like CommonSpirit Health, Atlantic Health, and Banner Health trust Innovaccer to integrate a system of intelligence into their existing infrastructure, extending the human touch in healthcare. For more information, visit www.innovaccer.com.
Check us out on YouTube, Glassdoor, LinkedIn, Instagram, and the Web</div>

4261- Data Engineer

Devoteam

<div>
 
 Tech for People Unlocks the Future
 
 
 
 At Devoteam, we believe that technology, combined with strong human values, can actively drive change for the better. Discover how Tech for People is shaping the future, creating a positive impact on individuals and the world around us.
 
 
 With over 25 years of passion for technology and a presence in 18+ countries across EMEA and beyond, we are committed to leveraging innovation, expertise, and human-centric values to make a difference.
 
 
 
 Devoteam Culture &amp; Values:
 
 
 
 True innovation is born from a powerful culture, fused with meaningful values.
 
 
 
 Culture:
 
 
 
 
 Fair and courageous
 
 
 
 Everyone is treated fairly &ndash; this fuels bravery. At Devoteam, we always make fair decisions. We listen and are willing to be challenged, taking courageous decisions as a result. We help our employees to progress at every step and congratulate those who deserve it.
 
 
 
 Ambition and results
 
 
 
 Ambition is nurtured at every step &ndash; this drives results. We are ambitious entrepreneurs with a taste for performance, growth and celebrating success. Commitments are always kept as we seek to achieve profitable growth to create value and employment. We aim to bring as much value as possible to our clients, at every touchpoint.
 
 
 
 Learning and innovating
 
 
 
 Curiosity and learning are at our core &ndash; this stimulates innovation. At Devoteam, we are curious. We learn and embrace innovation constantly to meet challenges and build partnerships of excellence.
 
 
 
 Caring and sharing
 
 
 
 A caring attitude is infused into our culture &ndash; this encourages sharing. We believe in the power of teams, we promote support and collaboration.
 
 
 At Devoteam, we care about our teams and want to work in a positive, productive environment. We support the development of talent and careers,
 
 
 
 Values:
 
 
 
 <ul>
 <li>
 Respect
 </li>
 <li>
 Frankness
 </li>
 <li>
 Passion
 
 
 
 </li>
 </ul>
 
 Job Description
 
 
 
 A Data Engineer is expected to develop, monitor, and optimize data quality rules and processes to ensure reliable and accurate enterprise data.
 
 
 They identify and resolve data anomalies through profiling, cleansing, and validation workflows.
 
 
 The role ensures that business decisions are driven by complete, consistent, and high-integrity data across systems.
 
 
 
 Key Responsibilities:
 
 
 
 <ul>
 <li>
 Design, implement, and maintain data quality frameworks, rules, and processes to ensure the accuracy, completeness, and reliability of enterprise data.
 </li>
 <li>
 Collaborate with data governance, MDM, and data integration teams to enforce consistent data quality standards across systems.
 </li>
 <li>
 Conduct data profiling, anomaly detection, and validation to identify quality gaps and root causes.
 </li>
 <li>
 Develop automated data quality checks and workflows for continuous monitoring and remediation.
 </li>
 <li>
 Define and manage key data quality metrics (DQ KPIs) and build dashboards to visualize performance trends.
 </li>
 <li>
 Document data quality rules, issue logs, and remediation actions as part of the data governance framework.
 </li>
 <li>
 Work closely with business data stewards and domain owners to define data quality expectations and acceptance thresholds.
 </li>
 <li>
 Support audits, compliance reviews, and data management maturity assessments by providing DQ evidence and reports.
 </li>
 <li>
 Lead the design and deployment of scalable data quality solutions across multiple data domains and systems.
 </li>
 <li>
 Define enterprise data quality standards, policies, and rule frameworks aligned with governance strategy.
 </li>
 <li>
 Establish data quality scorecards, thresholds, and escalation workflows for high-impact issues.
 </li>
 <li>
 Conduct root cause analysis and lead remediation programs for chronic data issues.
 </li>
 <li>
 Mentor junior engineers and promote data quality best practices across teams.
 </li>
 <li>
 Participate in compliance with the local data management regulations (e.g. NDMO, NDI).
 </li>
 <li>
 Design, build, and maintain scalable, secure, and robust data pipelines for efficient data ingestion and transformation, with a strong focus on building quality checks into the infrastructure itself.
 </li>
 <li>
 Collaborate with cross-functional and leadership teams (Data Scientists, Analysts, and Business Leaders) to translate complex business requirements into technical data quality solutions.
 </li>
 <li>
 Research, evaluate, and recommend new data quality tools, technologies, and practices to enhance the reliability, security, and scalability of the data infrastructure.
 
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Information Management, or related discipline.
 </li>
 <li>
 5+ years of experience in Data Quality, Data Governance, or Data Engineering roles.
 </li>
 <li>
 Proven hands-on experience with enterprise DQ tools (e.g., Informatica DQ/IDMC, Ataccama, Talend DQ, SAS DQ).
 </li>
 <li>
 Strong expertise in data profiling, rule design, standardization, and exception management.
 </li>
 <li>
 Proficiency in SQL and scripting (Python, Shell, or Scala) for advanced data validation.
 </li>
 <li>
 Deep understanding of data governance frameworks and collaboration with data stewards.
 </li>
 <li>
 Ability to design DQ dashboards, scorecards, and KPIs to monitor performance.
 </li>
 <li>
 Strong communication skills for presenting findings and recommendations to business stakeholders.
 </li>
 <li>
 Experience mentoring junior engineers or managing small DQ workstreams.
 </li>
 <li>
 CDMP Associate Certificate and/or Informatica IDQ Certificate and/or IDMC DQ Certificate
 </li>
 <li>
 Experience defining data quality strategy and embedding DQ into enterprise data platforms (MDM, DWH, Data Lake).
 </li>
 <li>
 Understanding of data lineage, root cause analysis, and impact assessment.
 </li>
 <li>
 Knowledge of metadata management and integration with data catalogs.
 </li>
 <li>
 Familiarity with regulatory and compliance requirements (e.g., NDMO, NDI).
 </li>
 <li>
 Ability to automate DQ workflows through orchestration or CI/CD pipelines.
 
 
 
 </li>
 </ul>
 
 Additional Information
 
 
 
 
 Business Unit: Data &amp; Intelligence
 
 
 
 
 Level: Mid - Senior Level
 
</div>

Data Engineer

Mirai, a Scopely company

<div>
 Our Generative AI products are only as good as the data behind them. This role owns that data layer from end to end: the pipelines that bring data in, the transformations that shape it, and the way it reaches retrieval systems, agents, and analytics. The work runs on AWS, and the aim is a single governed source that every consumer can rely on.
 
 
 We want someone who has already built data pipelines for AI systems, not only for reporting. Preparing data for an LLM or an agent brings its own work around chunking, embeddings, indexing, and keeping content current, and you have done it before. The team is small and spans several languages, so you will own your pipelines and help set the standards the rest of us follow.
 
 
 
 What You Will Do
 
 
 
 <ul>
 <li>
 Build and run the batch and streaming pipelines that move data from source systems into the lake and through to the warehouse, owning the layers in between from raw to curated, along with their schema, quality, and lineage
 </li>
 <li>
 Build the data layer behind retrieval: source connectors, document parsing, chunking, embedding generation, and vector indexing, including re-embedding when content changes
 </li>
 <li>
 Model curated, query-ready datasets and metrics so AI and analytics consumers work from one definition instead of each rebuilding the logic
 </li>
 <li>
 Add quality checks, validation, and monitoring so problems surface before they reach a model or a user
 </li>
 <li>
 Apply access control where it belongs: row and column level rules, PII handling, and entitlement-aware datasets, enforced as close to query time as the stack allows
 </li>
 <li>
 Work with the platform and DevOps engineers to expose data and retrieval as documented, dependable services
 </li>
 <li>
 Keep storage, compute, and query costs in check, with particular attention to the cost of embedding and vector workloads
 </li>
 <li>
 Review code, write the documentation, and help shape how the team builds its data layer
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Eight or more years in data engineering overall. That includes hands-on work building data for AI or ML systems such as retrieval, embeddings, or feature data, which can be a more recent part of your background
 </li>
 <li>
 Strong SQL and strong Python, including PySpark or similar distributed processing
 </li>
 <li>
 Production experience across the AWS data stack: S3 for the lake, Glue for ETL and the Data Catalog, Athena for serverless query, and Redshift as the warehouse
 </li>
 <li>
 Hands-on experience with a layered data architecture, whether you call it medallion (bronze, silver, gold), a data lake feeding a warehouse, or a lakehouse, including building the transformation stages that move data from raw to curated
 </li>
 <li>
 Experience with an ELT or integration tool such as Airbyte, Fivetran, or Meltano, including building or maintaining connectors
 </li>
 <li>
 Experience with event-driven pipelines using SQS and SNS, and with at least one streaming or change-data-capture technology such as Kinesis, Amazon MSK, or Debezium
 </li>
 <li>
 Hands-on experience with a semantic or metrics layer over the warehouse, such as Cube or the dbt Semantic Layer
 </li>
 <li>
 Hands-on experience with at least one vector store and embedding workflow: pgvector, Amazon OpenSearch, Pinecone, Weaviate, or Milvus
 </li>
 <li>
 Comfort with columnar and open table formats: Parquet together with Apache Iceberg, Delta Lake, or Hudi
 </li>
 <li>
 Working knowledge of an orchestrator such as Amazon MWAA, Step Functions, Dagster, or Prefect, and enough infrastructure as code to work closely with DevOps
 </li>
 </ul>
</div>

Senior Data Engineer

FlyAkeed

<div>
 
 About FlyAkeed:
 
 
 
 FlyAkeed is a leading online platform dedicated to simplifying the travel booking process for flights and hotels. Established in 2017 and headquartered in Riyadh, Saudi Arabia, we are committed to delivering an exceptional travel experience for our clients.
 
 
 
 Highlights:
 
 
 
 Current funding stage: Series A
 
 
 Supported by: PIF subsidiary Sanabil Investments, Elm, Artal Capital, Alrajhi Partners.
 
 
 
 Role Definition
 
 
 
 A Go-To-Market (GTM) Engineer is a hybrid technical and revenue-focused role that bridges Sales, Marketing, Growth, Revenue Operations, and Engineering. The role is responsible for designing, building, integrating, and automating the technical infrastructure that powers the buyer journey, from lead generation and data enrichment to AI-powered personalization, lead routing, pipeline management, and performance reporting.
 
 
 The GTM Engineer translates business requirements and growth strategies into scalable technical workflows that reduce manual work, improve data quality, accelerate sales execution, and drive repeatable revenue growth.
 
 
 
 Role Overview
 
 
 
 We are looking for a highly technical and business-minded GTM Engineer to join FlyAkeed's Growth team in Riyadh. This role sits at the intersection of revenue strategy, data, automation, and systems architecture. You will be responsible for building and optimizing the technical engine behind FlyAkeed's go-to-market operations, including CRM workflows, enrichment systems, outbound campaigns, AI-driven personalization, lead scoring, reporting dashboards, and integrations across the sales and marketing tech stack.
 
 
 The ideal candidate is comfortable working with both commercial teams and technical tools. You should be able to understand sales and marketing needs, convert them into automated workflows, and continuously improve the systems that help FlyAkeed scale its revenue engine across Saudi Arabia and the GCC.
 
 
 
 Key Responsibilities:
 
 
 
 
 GTM Systems &amp; Architecture
 
 
 
 <ul>
 <li>
 Design, build, integrate, and maintain FlyAkeed's GTM tech stack across CRM, marketing automation, outbound, enrichment, analytics, and sales productivity tools
 </li>
 <li>
 Ensure seamless data flow between systems such as HubSpot, Clay, n8n, Make, Smartlead, Lemlist, analytics tools, and other revenue platforms
 </li>
 <li>
 Translate business requirements from Sales, Marketing, Growth, and RevOps teams into scalable technical workflows
 </li>
 <li>
 dentify system gaps, workflow inefficiencies, and manual processes that can be automated or improved
 
 
 </li>
 </ul>
 
 Workflow Automation
 
 
 
 <ul>
 <li>
 Build and deploy automated workflows for lead capture, enrichment, scoring, qualification, routing, follow-up, and lifecycle management
 </li>
 <li>
 Create automation logic to assign high-priority leads or accounts to the right sales team members in a timely and accurate manner
 </li>
 <li>
 Automate repetitive sales and marketing operations to improve team productivity and execution speed
 </li>
 <li>
 Maintain documentation of GTM workflows, system logic, and automation rules
 
 
 </li>
 </ul>
 
 Lead Generation &amp; Outbound Operations
 
 
 
 <ul>
 <li>
 Build and manage prospecting systems using tools such as Clay, LinkedIn Sales Navigator, enrichment platforms, and outbound sequencing tools
 </li>
 <li>
 Support outbound campaign execution, including list building, segmentation, personalization workflows, sequencing, and performance tracking
 </li>
 <li>
 Improve account prioritization, lead qualification, and campaign targeting based on data and market signals
 </li>
 <li>
 Collaborate with Sales and Marketing teams to improve lead quality and conversion rates
 
 
 </li>
 </ul>
 
 AI Implementation &amp; Personalization
 
 
 
 <ul>
 <li>
 Design and implement AI-powered workflows to support account research, lead qualification, personalized outreach, sales enablement, and next-best-action recommendations
 </li>
 <li>
 Configure AI and LLM-based tools to generate relevant company insights, prospect summaries, personalized messaging, and campaign support
 </li>
 <li>
 Continuously test AI use cases that improve GTM efficiency, personalization, and sales productivity
 
 
 </li>
 </ul>
 
 Data Management &amp; CRM Operations
 
 
 
 <ul>
 <li>
 Own CRM data hygiene, segmentation, deduplication, enrichment, validation rules, and lifecycle stage management
 </li>
 <li>
 Ensure clean and reliable data across GTM systems to support accurate reporting and decision-making
 </li>
 <li>
 Manage lead source tracking, UTM tracking, form capture, field mapping, and campaign attribution
 </li>
 <li>
 Support data governance and improve consistency across sales and marketing operations
 
 
 </li>
 </ul>
 
 Analytics, Reporting &amp; Experimentation
 
 
 
 <ul>
 <li>
 Build dashboards and reports to track pipeline health, campaign performance, funnel conversion, lead quality, sales productivity, and revenue impact
 </li>
 <li>
 Monitor GTM performance and identify opportunities to improve conversion rates across the buyer journey
 </li>
 <li>
 Run experiments across outbound, lead scoring, personalization, routing, and campaign workflows
 </li>
 <li>
 Provide insights and recommendations to support better GTM decision-making
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 Minimum 3 years of hands-on experience in GTM Engineering, Revenue Operations, Marketing Operations, Sales Operations, Growth Operations, or a similar technical growth role
 </li>
 <li>
 Strong experience with CRM platforms, preferably HubSpot
 </li>
 <li>
 Hands-on experience with automation tools such as Clay, n8n, Make, Zapier, or similar platforms
 </li>
 <li>
 Familiarity with outbound, enrichment, and prospecting tools such as Clay, Smartlead, Lemlist, or similar
 </li>
 <li>
 Strong understanding of B2B sales funnels, lead generation, pipeline management, sales processes, and campaign operations
 </li>
 <li>
 Ability to build workflows, manage data structures, clean datasets, and design segmentation logic
 </li>
 <li>
 Strong data literacy with the ability to analyze funnel performance, campaign results, and pipeline metrics
 </li>
 <li>
 Comfortable using AI tools and LLMs for research, personalization, automation, and productivity
 </li>
 <li>
 Strong problem-solving skills with the ability to convert business needs into scalable technical systems
 </li>
 <li>
 Good communication skills and ability to work cross-functionally with Sales, Marketing,Growth, RevOps, and Product teams
 </li>
 <li>
 Based in or willing to relocate to Riyadh, Saudi Arabia
 </li>
 </ul>
</div>

GTM Engineer

<div>About FlyAkeed:
FlyAkeed is a leading online platform dedicated to simplifying the travel booking process for flights and hotels. Established in 2017 and headquartered in Riyadh, Saudi Arabia, we are committed to delivering an exceptional travel experience for our clients.
Highlights:
Current funding stage: Series A
Supported by: PIF subsidiary Sanabil Investments, Elm, Artal Capital, Alrajhi Partners. 
 
Role Definition
A Go-To-Market (GTM) Engineer is a hybrid technical and revenue-focused role that bridges Sales, Marketing, Growth, Revenue Operations, and Engineering. The role is responsible for designing, building, integrating, and automating the technical infrastructure that powers the buyer journey, from lead generation and data enrichment to AI-powered personalization, lead routing, pipeline management, and performance reporting. 
The GTM Engineer translates business requirements and growth strategies into scalable technical workflows that reduce manual work, improve data quality, accelerate sales execution, and drive repeatable revenue growth. 
Role Overview
We are looking for a highly technical and business-minded GTM Engineer to join FlyAkeed&rsquo;s Growth team in Riyadh. This role sits at the intersection of revenue strategy, data, automation, and systems architecture. You will be responsible for building and optimizing the technical engine behind FlyAkeed&rsquo;s go-to-market operations, including CRM workflows, enrichment systems, outbound campaigns, AI-driven personalization, lead scoring, reporting dashboards, and integrations across the sales and marketing tech stack. 
 
The ideal candidate is comfortable working with both commercial teams and technical tools. You should be able to understand sales and marketing needs, convert them into automated workflows, and continuously improve the systems that help FlyAkeed scale its revenue engine across Saudi Arabia and the GCC. 
Key Responsibilities:
GTM Systems &amp; Architecture<ul><li>
Design, build, integrate, and maintain FlyAkeed&rsquo;s GTM tech stack across CRM, marketing automation, outbound, enrichment, analytics, and sales productivity tools.</li><li>
Ensure seamless data flow between systems such as HubSpot, Clay, n8n, Make, Smartlead, Lemlist, analytics tools, and other revenue platforms.</li><li>
Translate business requirements from Sales, Marketing, Growth, and RevOps teams into scalable technical workflows.</li><li>
dentify system gaps, workflow inefficiencies, and manual processes that can be automated or improved. 
 
Workflow Automation</li></ul><ul><li>
Build and deploy automated workflows for lead capture, enrichment, scoring, qualification, routing, follow-up, and lifecycle management.</li><li>
Create automation logic to assign high-priority leads or accounts to the right sales team members in a timely and accurate manner.</li><li>
Automate repetitive sales and marketing operations to improve team productivity and execution speed.</li><li>
Maintain documentation of GTM workflows, system logic, and automation rules.
 
 
Lead Generation &amp; Outbound Operations</li></ul><ul><li>
Build and manage prospecting systems using tools such as Clay, LinkedIn Sales Navigator, enrichment platforms, and outbound sequencing tools.</li><li>
Support outbound campaign execution, including list building, segmentation, personalization workflows, sequencing, and performance tracking.</li><li>
Improve account prioritization, lead qualification, and campaign targeting based on data and market signals.</li><li>
Collaborate with Sales and Marketing teams to improve lead quality and conversion rates 
 
AI Implementation &amp; Personalization</li></ul><ul><li>
Design and implement AI-powered workflows to support account research, lead qualification, personalized outreach, sales enablement, and next-best-action recommendations.</li><li>
Configure AI and LLM-based tools to generate relevant company insights, prospect summaries, personalized messaging, and campaign support.</li><li>
Continuously test AI use cases that improve GTM efficiency, personalization, and sales productivity.</li></ul>
Data Management &amp; CRM Operations<ul><li>
Own CRM data hygiene, segmentation, deduplication, enrichment, validation rules, and lifecycle stage management.</li><li>
Ensure clean and reliable data across GTM systems to support accurate reporting and decision-making.</li><li>
Manage lead source tracking, UTM tracking, form capture, field mapping, and campaign attribution.</li><li>
Support data governance and improve consistency across sales and marketing operations.
 
 
Analytics, Reporting &amp; Experimentation</li></ul><ul><li>
Build dashboards and reports to track pipeline health, campaign performance, funnel conversion, lead quality, sales productivity, and revenue impact.</li><li>
Monitor GTM performance and identify opportunities to improve conversion rates across the buyer journey.</li><li>
Run experiments across outbound, lead scoring, personalization, routing, and campaign workflows.</li><li>
Provide insights and recommendations to support better GTM decision-making.</li></ul> 

Benefits 
<ul><li>
Minimum 3 years of hands-on experience in GTM Engineering, Revenue Operations, Marketing Operations, Sales Operations, Growth Operations, or a similar technical growth role.</li><li>
Strong experience with CRM platforms, preferably HubSpot.</li><li>
Hands-on experience with automation tools such as Clay, n8n, Make, Zapier, or similar platforms.</li><li>
Familiarity with outbound, enrichment, and prospecting tools such as Clay, Smartlead, Lemlist, or similar.</li><li>
Strong understanding of B2B sales funnels, lead generation, pipeline management, sales processes, and campaign operations.</li><li>
Ability to build workflows, manage data structures, clean datasets, and design segmentation logic.</li><li>
Strong data literacy with the ability to analyze funnel performance, campaign results, and pipeline metrics.</li><li>
Comfortable using AI tools and LLMs for research, personalization, automation, and productivity.</li><li>
Strong problem-solving skills with the ability to convert business needs into scalable technical systems.</li><li>
Good communication skills and ability to work cross-functionally with Sales, Marketing,Growth, RevOps, and Product teams.</li><li>
Based in or willing to relocate to Riyadh, Saudi Arabia.</li></ul></div>

Cognizant

Role Overview
 As a Senior Data Engineer / Tech Lead, you will design, develop, and optimize scalable, enterprise-grade cloud-native data platforms and pipelines on the Microsoft Azure ecosystem . You will possess deep technical ownership and be responsible for implementing modern data architectures (such as Lakehouse and Medallion architecture) . This role requires close collaboration with architects, business analysts, and downstream data consumers to translate complex business requirements into high-performing and secure data solutions.
 
Key Responsibilities
 1.Data Pipeline Design & Orchestration (ADF)
 <ul>
<li>Design, build, and maintain complex, scalable ETL/ELT pipelines using Azure Data Factory (ADF) to ingest heterogeneous data from diverse sources (APIs, SFTP, Oracle Fusion, SQL Server, Event Hubs, etc.)</li>
<li>Implement parameter-driven dynamic pipelines, custom activities, and robust scheduling triggers</li>
<li>Configure and manage Integration Runtimes (Self-Hosted and Azure IR) for secure and efficient on-premise to cloud data movement</li>
</ul>
2.Advanced Big Data Processing (Azure Databricks)
 <ul>
<li>Develop high-performance batch and real-time streaming data pipelines using Azure Databricks, PySpark, Spark SQL, or Scala</li>
<li>Implement Medallion Architecture (Bronze, Silver, and Gold layers) and maintain modern Lakehouse architectures utilizing Delta Lake</li>
<li>Optimize Spark compute usage through parameter-driven jobs, proper cluster scaling, and Databricks serverless compute configurations</li>
<li>Perform deep performance tuning, query optimization, and memory management of heavy Spark workloads</li>
</ul>
3.Data Warehousing & Modeling
 <ul>
<li>Design and refine data models including dimensional modeling, star schemas, and Slowly Changing Dimensions (SCDs)</li>
<li>Optimize databases by writing complex, performant T-SQL queries, stored procedures, and schemas on Azure SQL Database or Azure Synapse Analytics</li>
</ul>
4.Data Governance, Security & DevOps
 <ul>
<li>Enforce data governance, lineage, and access controls across the platform utilizing Unity Catalog .</li>
<li>Secure data architectures utilizing Azure Key Vault, Managed Identities, Service Principals, and VNET-integrated environments</li>
<li>Implement CI/CD pipelines using Git and Azure DevOps to automate database and pipeline deployments</li>
</ul>
5.Leadership & Collaboration
 <ul>
<li>Provide technical mentorship and guidance to junior developers and QA teams</li>
<li>Enforce engineering discipline through standard code reviews, structured pre/post-deployment validations, and thorough documentation</li>
</ul>
Required Skills & Qualifications
 <ul>
<li>Overall Experience: Minimum of 8+ years of professional experience in Data Engineering or Data Warehousing</li>
<li>Azure Experience: 4+ years of dedicated, hands-on experience designing and operating modern data platforms on Microsoft Azure</li>
<li>Programming Languages: Proficient in Python/PySpark, SQL (advanced query optimization, indexing, stored procedures), and optionally Scala</li>
<li>Core Azure Stack: Extensive knowledge of Azure Data Factory, ADLS Gen2, Azure Databricks (Delta Lake), Azure SQL Database, and Azure Synapse Analytics</li>
<li>Big Data Concepts: Robust understanding of Apache Spark architecture, distributed computing, and the Hadoop ecosystem</li>
<li>Data Integration: Strong background in CDC (Change Data Capture) mechanisms, API integrations, and event-driven data streaming (e.g., Event Hubs/Kafka)</li>
<li>Soft Skills: Excellent analytical capabilities, strong documentation skills, and the ability to articulate technical strategies to non-technical business partners</li>
</ul>
Preferred / "Good-to-Have" Qualifications
 <ul>
<li>Certifications: Microsoft Certified: Azure Data Engineer Associate (DP-203), Azure Solutions Architect Expert, or Databricks Certified Associate/Professional</li>
<li>Cloud Platforms: Exposure to multi-cloud environments (e.g., Google Cloud Platform or AWS)</li>
<li>IaC: Experience using Infrastructure as Code (IaC) tools like Terraform or ARM Templates to deploy Azure resources</li>
</ul>

Architect

VaporVM

<div><div>Date Posted: 11 June, 2026
</div><div>Industry: IT Services and IT Consulting
</div><div>Location: VaporVM</div></div>
 <div><h2 class="jobSectionHeader">Job Description:</h2>
<div><h1 class="jobSectionHeader">Senior HPC / Infrastructure Engineer</h1>
Location: Riyadh, Saudi Arabia
Employment Type: Full-Time
Experience: 10+ Years (Hands-On)
<h2 class="jobSectionHeader">Position Overview</h2>
We are seeking a highly experienced Senior HPC / Infrastructure Engineer with proven expertise in designing, deploying, and operating enterprise-scale High-Performance Computing (HPC) and AI infrastructure environments. This role is ideal for a hands-on technical leader who has built and managed production-grade HPC platforms, GPU clusters, Kubernetes ecosystems, and AI infrastructure from the ground up.
The successful candidate will play a critical role in architecting, optimizing, and maintaining mission-critical compute environments that support advanced AI/ML, data science, and high-performance workloads.
<h2 class="jobSectionHeader">Required Certifications</h2>
<ul><li>RHCE &ndash; Red Hat Certified Engineer (Active)</li>
<li>CKA &ndash; Certified Kubernetes Administrator (Active)</li>
</ul><h2 class="jobSectionHeader">Core Technical Expertise</h2>
<h3 class="jobSectionHeader">HPC &amp; NVIDIA AI Ecosystem</h3>
<ul><li>NVIDIA Base Command Manager (BCM)</li>
<li>NVIDIA AI Enterprise</li>
<li>NVIDIA GPU Operator &amp; Network Operator</li>
<li>NVIDIA NIM Inference Services</li>
<li>NVIDIA AI Blueprints</li>
<li>CUDA, GPU Drivers, and Performance Optimization</li>
</ul><h3 class="jobSectionHeader">Compute &amp; Container Platforms</h3>
<ul><li>Kubernetes (Architecture, Operations &amp; Scaling)</li>
<li>Slurm Workload Manager</li>
<li>Distributed Computing Environments</li>
</ul><h3 class="jobSectionHeader">Operating Systems</h3>
<ul><li>Red Hat Enterprise Linux (RHEL)</li>
<li>Ubuntu LTS (Canonical)</li>
</ul><h3 class="jobSectionHeader">Automation &amp; DevOps</h3>
<ul><li>CI/CD Pipeline Design &amp; Implementation</li>
<li>Infrastructure Automation</li>
<li>Platform Lifecycle Management</li>
<li>Configuration Management &amp; Orchestration</li>
</ul><h2 class="jobSectionHeader">Key Responsibilities</h2>
<ul><li>Design, deploy, and operate large-scale HPC and AI infrastructure environments from bare metal through workload orchestration.</li>
<li>Architect and manage NVIDIA GPU platforms, including BCM, AI Enterprise, GPU Operator, and AI service enablement.</li>
<li>Configure, optimize, and maintain Slurm scheduling environments for high-throughput and GPU-intensive workloads.</li>
<li>Design and operate highly available Kubernetes clusters supporting AI/ML, analytics, and containerized workloads.</li>
<li>Enable and support NVIDIA NIM services and AI Blueprint deployments for enterprise AI initiatives.</li>
<li>Administer and optimize RHEL and Ubuntu environments, ensuring stability, security, and performance.</li>
<li>Develop and maintain infrastructure automation frameworks and CI/CD pipelines for platform and application deployment.</li>
<li>Optimize performance across compute, GPU, storage, networking, and cluster resources.</li>
<li>Implement monitoring, observability, alerting, capacity planning, and operational best practices.</li>
<li>Enforce security, patch management, access controls, and compliance standards across the infrastructure stack.</li>
<li>Lead troubleshooting, root cause analysis, and resolution of complex infrastructure and platform issues.</li>
</ul><h2 class="jobSectionHeader">Candidate Profile</h2>
<ul><li>10+ years of hands-on experience in HPC, Linux infrastructure, and enterprise platform engineering.</li>
<li>Proven track record of building and operating production-scale HPC, GPU, or AI infrastructure environments.</li>
<li>Deep expertise in Kubernetes, Slurm, Linux administration, and NVIDIA AI technologies.</li>
<li>Strong understanding of distributed systems, workload scheduling, cluster management, and performance optimization.</li>
<li>Experience supporting AI/ML, data science, and high-performance computing workloads at scale.</li>
<li>Strong analytical, troubleshooting, and problem-solving skills.</li>
<li>Ability to work across infrastructure, platform, automation, and AI enablement domains.</li>
<li>Demonstrated ownership mindset with a history of delivering reliable, scalable, and high-performing solutions.</li></ul></div></div>

Senior Infrastructure / HPC

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