data engineer

Easygenerator

<div>
 
 Join Easygenerator and build the data platform powering the future of learning
 
 
 
 Step into an exciting role with an innovative e-learning software company in the EdTech space as a
 
 Data Engineer
 
 .
 
 
 Easygenerator is a fast-growing scale-up revolutionizing e-learning with our award-winning authoring tool. Join us to build scalable data solutions that enable smarter decisions across Product, Marketing, Revenue, and Business Intelligence.
 
 
 What's in it for you?
 
 
 <ul>
 <li>
 Grow Your Career: Take ownership of our modern data platform and work on high-impact projects spanning analytics, AI, and business intelligence.
 </li>
 <li>
 International Environment: Join a dynamic, international team (40+ nationalities) in a fast-growing scale-up where your work directly influences business outcomes.
 </li>
 <li>
 AI-First Company: We embrace AI in both our product and internal operations. You'll gain hands-on experience with AI-powered analytics and emerging data technologies.
 </li>
 <li>
 Learning &amp; Development: Access continuous coaching, learning opportunities, and the freedom to explore new technologies and best practices.
 </li>
 <li>
 Hybrid Working Policy: 3 day on-site / 2-day Work from Home (WFH) split.
 
 
 </li>
 </ul>
 What you will be doing
 
 
 <ul>
 <li>
 Build and maintain scalable data pipelines and infrastructure using Snowflake, AWS Glue, and modern ETL/ELT frameworks.
 </li>
 <li>
 Integrate data from platforms such as Salesforce, Mixpanel, Segment, Customer.io, Intercom, Google Analytics, and LinkedIn Ads.
 </li>
 <li>
 Develop reliable data models, warehouses, and data lakes to support reporting and analytics.
 </li>
 <li>
 Implement data quality, monitoring, governance, and security best practices.
 </li>
 <li>
 Build AI-powered self-service analytics capabilities for business users.
 </li>
 <li>
 Partner with Product, Marketing, Revenue Operations, and BI teams to deliver impactful data solutions.
 </li>
 <li>
 Optimize platform performance, reliability, and cost efficiency.
 
 
 </li>
 </ul>
 What you will bring
 
 
 <ul>
 <li>
 5+ years of Data Engineering experience.
 </li>
 <li>
 Strong expertise in Snowflake, including architecture, performance optimization, governance, and security.
 </li>
 <li>
 Experience with AWS Glue (PySpark), ETL/ELT pipelines, and workflow orchestration.
 </li>
 <li>
 Advanced SQL and Python skills.
 </li>
 <li>
 Experience with PostgreSQL, MongoDB, Amazon S3, and modern cloud data architectures.
 </li>
 <li>
 Strong understanding of data modelling, warehousing, and analytics engineering practices.
 </li>
 <li>
 Experience integrating SaaS platforms and customer, product, marketing, or revenue data.
 </li>
 <li>
 Knowledge of data governance, privacy, and compliance frameworks such as GDPR.
 </li>
 <li>
 Strong problem-solving skills, ownership mindset, and attention to detail.
 
 
 </li>
 </ul>
 Nice to have
 
 
 <ul>
 <li>
 Experience in a B2B SaaS environment.
 </li>
 <li>
 Power BI experience, including data modeling and DAX.
 </li>
 <li>
 Experience with Snowflake Cortex AI and AI-powered analytics solutions.
 </li>
 <li>
 Knowledge of marketing attribution and revenue analytics.
 </li>
 <li>
 Experience with Streamlit, Mixpanel, or similar analytics tools.
 
 
 </li>
 </ul>
 Ready to Join Us?
 
 
 If you're passionate about building modern data platforms and helping teams make smarter decisions with data, we'd love to hear from you. Apply today!
 
 
</div>

Data Engineer

DATAMAZE . AI

<div>
 Hyderabad, India / Dubai, UAE
 
 
 Full-time
 
 
 Apply to Job
 
 
 
 About The Role
 
 
 
 We are looking for a highly motivated Machine Learning Engineer / Data Scientist to join our dynamic team. In this mid-level role, you will leverage your expertise in data science and machine learning to design, build, and deploy innovative models and solutions that address real-world challenges.
 
 
 You will collaborate with cross-functional teams, including data engineers, product managers, and software developers, to turn complex datasets into actionable insights and build machine learning solutions that drive business value. This is a fantastic opportunity to work on impactful projects, expand your skill set, and contribute to cutting-edge advancements in AI and data science.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Model Development: Design, train, and evaluate machine learning models to solve business problems such as classification, regression, clustering, and recommendation.
 </li>
 <li>
 Data Preparation: Work with large and complex datasets, performing data cleaning, preprocessing, and feature engineering to optimize model performance.
 </li>
 <li>
 Model Deployment: Deploy machine learning models into production environments, ensuring scalability and robustness.
 </li>
 <li>
 Algorithm Selection: Research and implement state-of-the-art algorithms and methodologies to enhance model accuracy and efficiency.
 </li>
 <li>
 Collaboration: Collaborate with data engineering teams to build data pipelines and ensure efficient data flow for machine learning workflows.
 </li>
 <li>
 Visualization and Reporting: Create clear and actionable visualizations and reports to communicate findings and results to stakeholders.
 </li>
 <li>
 Monitoring and Maintenance: Monitor model performance in production, address drift or bias issues, and optimize models as needed.
 </li>
 <li>
 Tool Development: Build tools and frameworks to enable rapid experimentation and iteration of machine learning models.
 </li>
 <li>
 Documentation: Maintain comprehensive documentation for models, experiments, and processes.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 Education:
 
 
 
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Science, Machine Learning, Statistics, or a related field (or equivalent experience).
 
 
 
 Technical Skills
 
 
 
 <ul>
 <li>
 Strong programming skills in Python, R, or similar languages.
 </li>
 <li>
 Experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, Scikit-learn, or Keras.
 </li>
 <li>
 Proficiency in data manipulation and analysis using tools like Pandas, NumPy, and SQL.
 </li>
 <li>
 Experience with big data technologies such as Spark, Hadoop, or similar.
 </li>
 <li>
 Knowledge of cloud platforms and services (e.g., AWS SageMaker, Google AI Platform, Azure ML).
 </li>
 <li>
 Familiarity with MLOps practices and tools for CI/CD in machine learning workflows.
 </li>
 <li>
 Understanding of data visualization tools like Matplotlib, Seaborn, or Tableau.
 </li>
 <li>
 Strong grasp of statistical methods, probability, and optimization techniques.
 
 
 </li>
 </ul>
 
 Experience
 
 
 
 <ul>
 <li>
 3&ndash;5 years of experience in machine learning, data science, or a related field.
 </li>
 <li>
 Proven experience building and deploying machine learning models in production.
 </li>
 <li>
 Experience with natural language processing (NLP), computer vision, or time-series analysis is a plus.
 
 
 </li>
 </ul>
 
 Soft Skills
 
 
 
 <ul>
 <li>
 Strong problem-solving and analytical thinking abilities.
 </li>
 <li>
 Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
 </li>
 <li>
 Ability to work independently and collaboratively within a team.
 </li>
 <li>
 Curiosity and eagerness to stay updated on the latest advancements in machine learning and AI.
 
 
 </li>
 </ul>
 
 About The Company
 
 
 
 Datamaze is a dynamic company specializing in AI, Data, and Analytics consulting services. We are dedicated to transforming businesses by leveraging the power of data and artificial intelligence. With a team of industry experts in technology, business strategy, and data science, Datamaze offers a range of services including data strategy development, AI model creation, advanced analytics, and data visualization. Our approach is client-centric, focusing on creating customized solutions that address unique business challenges and objectives. The team, comprising data scientists, AI experts, strategists, and engineers, is committed to continuous learning and innovation.
 
 
 Datamaze positions itself as a trusted partner for businesses looking to navigate the complex data and AI landscape, aiming to optimize operations, inform decision-making, and maintain a competitive edge.
 
 
 Apply Now
</div>

Machine Learning Engineer / Data Scientist (Mid-Level)

Group AMANA

<div>
 
 Amana is seeking an experienced Data Platform Lead with deep expertise in Databricks, the Microsoft Azure ecosystem, and modern lakehouse architectures. The ideal candidate will play a central role in Amana's ongoing platform refresh, moving workloads from Synapse Analytics to a Databricks lakehouse with Unity Catalog, and building the technical foundation that powers analytics, AI, and governance across the enterprise. This role sits within Amana's Data Science, Governance &amp; AI Centre of Excellence, working alongside architects, engineers, analysts, data scientists, and AI engineers, with future growth opportunities into senior platform leadership.
 
 
 
 
 
 
 Why This Role Matters
 
 
 
 Amana operates across capital-intensive sectors where data reliability, cost discipline, and speed of insight are business-critical. The enterprise data platform is the backbone of every downstream analytics, AI, and governance initiative &mdash; from ERP-integrated reporting and predictive models to Agentic AI and Copilot rollouts across the group.
 
 
 You will be at the technical centre of this transformation, designing, building, and hardening the lakehouse that the rest of the function depends on.
 
 
 
 
 
 
 Core Responsibilities
 
 
 
 
 Lakehouse Architecture &amp; Delivery
 
 
 <ul>
 <li>
 Design and deliver end-to-end Databricks lakehouse components &mdash; ingestion, transformation, semantic layer, and serving.
 </li>
 <li>
 Set and enforce Delta Lake and medallion architecture standards across bronze, silver, and gold layers.
 </li>
 <li>
 Lead the technical execution of the Synapse Analytics to Databricks migration, including parallel run, cutover, and decommissioning.
 </li>
 <li>
 Contribute to and sign off on reference designs, integration patterns, and architecture decision records.
 </li>
 </ul>
 
 
 
 
 
 Data Engineering &amp; Integration
 
 
 <ul>
 <li>
 Build and maintain robust ingestion and transformation pipelines from Amana's core enterprise systems: Oracle Fusion (Finance, HCM, P2P, CRM), Hyperion, CMiC, project and operations systems, SharePoint, and Power Platform.
 </li>
 <li>
 Apply strong CI/CD, DataOps, and infrastructure-as-code practices using Git, Azure DevOps, and Terraform or Bicep.
 </li>
 <li>
 Ensure platform reliability through monitoring, alerting, and structured incident response.
 </li>
 </ul>
 
 
 
 
 
 AI/ML &amp; Analytics Enablement
 
 
 <ul>
 <li>
 Build and operate feature store, MLOps, and LLMOps foundations on Databricks.
 </li>
 <li>
 Enable production-grade RAG, agent, and Copilot patterns in partnership with the Data Scientist and AI Engineer.
 </li>
 <li>
 Deliver Power BI semantic models, certified datasets, and self-service guardrails supporting the Amana Digital Academy and enterprise adoption.
 </li>
 </ul>
 
 
 
 
 
 Data Governance &amp; Trustworthy Data
 
 
 <ul>
 <li>
 Implement lineage, cataloguing, access control, data quality, and PDPL controls inside the platform using Unity Catalog and Microsoft Purview.
 </li>
 <li>
 Partner with the Data Governance Office to translate live policies into enforceable platform controls.
 </li>
 <li>
 Support regulatory, ethical, and internal compliance obligations across the data estate.
 </li>
 </ul>
 
 
 
 
 
 Cloud &amp; Cost Discipline
 
 
 <ul>
 <li>
 Own FinOps hygiene on the platform: cluster policies, workload tiering, rightsizing, and chargeback readiness.
 </li>
 <li>
 Translate cloud cost outcomes into commercial terms understood by finance and business stakeholders.
 </li>
 </ul>
 
 
 
 
 
 Collaboration &amp; Technical Leadership
 
 
 <ul>
 <li>
 Work closely with the Data Architect, Data Engineer, Data Analyst, Data Scientist, and AI Engineer to set and uphold technical standards.
 </li>
 <li>
 Provide hands-on technical guidance and code review across the team.
 </li>
 <li>
 Translate business requirements into technical designs with clear delivery outcomes.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications
 
 
 <ul>
 <li>
 Minimum of 7 years in data engineering or data platform work, with strong hands-on delivery experience.
 </li>
 <li>
 At least 3 years hands-on with Databricks, Apache Spark, and Delta Lake at enterprise scale. Snowflake or BigQuery experience is acceptable where the CV shows a real Databricks migration.
 </li>
 <li>
 Contributed to the build or rebuild of an enterprise data platform serving multiple business domains.
 </li>
 <li>
 Deep hands-on experience with the Azure data stack: Databricks, ADLS, Azure Data Factory, Synapse, Azure SQL, Fabric.
 </li>
 <li>
 Direct experience integrating heavy ERP sources: Oracle Fusion, Hyperion, CMiC, or equivalent estates.
 </li>
 <li>
 Governance shipped to production using Unity Catalog or Microsoft Purview, with PDPL or GDPR controls operational, not theoretical.
 </li>
 <li>
 Practical FinOps outcomes on cloud spend.
 </li>
 <li>
 Strong on CI/CD, Git, Azure DevOps, and infrastructure-as-code (Terraform or Bicep).
 </li>
 <li>
 Excellent written and verbal communication skills across technical and business audiences.
 </li>
 </ul>
 
 
 
 
 
 Preferred Qualifications
 
 
 <ul>
 <li>
 Direct experience of a Synapse Analytics to Databricks migration.
 </li>
 <li>
 Exposure to MLOps and LLMOps stacks: MLflow, feature store, vector stores, RAG, agent frameworks.
 </li>
 <li>
 Familiarity with Power BI semantic models and enterprise BI governance.
 </li>
 <li>
 Streaming and event-driven experience: Kafka, Event Hubs, Structured Streaming.
 </li>
 <li>
 Multi-entity, multi-country group exposure with mixed data residency considerations.
 </li>
 <li>
 Industry experience in construction, engineering services, manufacturing, energy, or logistics.
 </li>
 </ul>
 
 
 
 
 
 Certifications
 
 
 
 
 
 Mandatory:
 
 
 
 <ul>
 <li>
 
 Databricks Certified Data Engineer Professional
 
 (Candidates holding the Associate level will be considered on the condition that Professional is achieved within 6 months of joining.)
 </li>
 </ul>
 
 
 Preferred (one or more):
 
 
 <ul>
 <li>
 
 Databricks Certified Machine Learning Professional
 
 </li>
 <li>
 
 Databricks Certified Generative AI Engineer Associate
 
 </li>
 <li>
 
 Microsoft Certified: Azure Data Engineer Associate
 
 (DP-203 / DP-700)
 </li>
 <li>
 
 Microsoft Certified: Fabric Analytics Engineer Associate
 
 (DP-600)
 </li>
 <li>
 
 Microsoft Certified: Azure Solutions Architect Expert
 
 </li>
 <li>
 
 Certified Data Management Professional (CDMP)
 
 &mdash; DAMA
 </li>
 </ul>
 
 
 Education
 
 
 
 M.Tech / B.E. / B.Tech (Computer Science, Information Systems, IT) / MCA / MCS.
 
</div>

Data Platform Lead

Delivery Hero

<div>Company Description 
Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat&rsquo;s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.
We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.
Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner. 
Job Description 
As the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users. 
 
As a Senior Analytics Engineer, you will be responsible for transforming raw data into well-structured, reliable, and accessible data models that enable analysts, data scientists, and business stakeholders to make informed decisions. You will work closely with data engineers to build scalable data pipelines and collaborate with analysts to ensure data is actionable and insightful.<ul><li>
Design, build, and maintain clean, efficient, and scalable data models in SQL and dbt. Optimize query performance and data processing efficiency.</li><li>
Ensure data is structured to support self-service analytics and business intelligence.</li><li>
Work closely with data engineers to define data requirements and enhance ETL pipelines.</li><li>
Partner with product analysts, data scientists, and business teams to ensure data meets analytical and reporting needs.</li><li>
Implement and enforce data quality best practices to ensure accuracy and consistency.</li><li>
Develop and maintain data transformation workflows using dbt, SQL, and cloud-based data platforms. Automate data validation and reporting processes.</li><li>
Monitor data integrity and troubleshoot data issues proactively. Advocate for best practices in documentation, testing, and version control.</li></ul> 
Qualifications<ul><li> 
Bachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.</li><li>
Strong proficiency in Python, SQL and experience with dbt for data modeling.</li><li>
Experience working with cloud-based data warehouses (e.g., Snowflake, BigQuery, GCP, Redshift).</li><li>
Familiarity with version control (Git) and CI/CD practices for data workflows.</li><li>
Understanding of data engineering principles, including ETL/ELT processes.</li></ul></div>

Senior Analytics Engineer

Dicetek LLC

<div>
 
 Summary Of Role
 
 
 
 <ul>
 <li>
 Co-development of analytical engines based on statistical and machine learning algorithms
 </li>
 <li>
 Creation of sustainable digital solutions integrated with existing IT infrastructure in collaboration with business
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Conducts analytical experiments methodically with guidance from technology lead to help solve various problems and make a true impact across multiple domains and situations
 </li>
 <li>
 Process relevant data sources and build clear data-cleaning pipelines to feed data points and variables to the models in a well-structured format
 </li>
 <li>
 Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve models, and clean and validate data for uniformity and accuracy for visualization to business
 </li>
 <li>
 Analyze data for trends and patterns, apply statistical and machine learning algorithms, and interpret data with a clear objective in mind in line with project goals and milestones
 </li>
 <li>
 Support the deployment of analytical models into existing IT infrastructure by collaborating with DevOps engineers and Product owners
 </li>
 <li>
 Maintain delivered solutions sustainability after the development phase
 
 
 </li>
 </ul>
 
 ﻿Required Qualifications &amp; Experience
 
 
 
 <ul>
 <li>
 Bachelor's or Master's degree in information systems, data analytics, data science, computer science, economics, risk management or another quantitative related field
 </li>
 <li>
 Experience with Excel, SQL, Python, basic BI-development
 </li>
 <li>
 Proficiency in data processing (Pandas), statistical analysis, and machine learning algorithms
 </li>
 <li>
 Knowledge in building data processing pipelines &amp; ETLs
 </li>
 <li>
 Experience in implementing predictive engines with a focus on time-series forecast
 </li>
 <li>
 Experience in writing API calls based on specifications
 </li>
 <li>
 Experience in automated testing, ability to write mock and unit tests to test both model inputs and outputs
 </li>
 <li>
 Effective collaboration, experience in working with Scrum/Agile teams &amp; task tracking
 
 
 </li>
 </ul>
 
 Additional Considerations
 
 
 
 <ul>
 <li>
 The preferred profile is "all-the-way-rounder" rather than a person with deep expertise in only something specific
 </li>
 </ul>
</div>

Data Scientist (Arabic Speaker)

DICETEK LLC

<div>Summary of role<ul><li>Co-development of analytical engines based on statistical and machine learning algorithms</li><li>Creation of sustainable digital solutions integrated with existing IT infrastructure in collaboration with business</li></ul>
Responsibilities<ul><li>Conducts analytical experiments methodically with guidance from technology lead to help solve various problems and make a true impact across multiple domains and situations</li><li>Process relevant data sources and build clear data-cleaning pipelines to feed data points and variables to the models in a well-structured format</li><li>Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve models, and clean and validate data for uniformity and accuracy for visualization to business</li><li>Analyze data for trends and patterns, apply statistical and machine learning algorithms, and interpret data with a clear objective in mind in line with project goals and milestones</li><li>Support the deployment of analytical models into existing IT infrastructure by collaborating with DevOps engineers and Product owners</li><li>Maintain delivered solutions sustainability after the development phase</li></ul> 
﻿Required Qualifications &amp; experience<ul><li>Bachelor's or Master's degree in information systems, data analytics, data science, computer science, economics, risk management or another quantitative related field</li><li>Experience with Excel, SQL, Python, basic BI-development</li><li>Proficiency in data processing (Pandas), statistical analysis, and machine learning algorithms</li><li>Knowledge in building data processing pipelines &amp; ETLs</li><li>Experience in implementing predictive engines with a focus on time-series forecast</li><li>Experience in writing API calls based on specifications</li><li>Experience in automated testing, ability to write mock and unit tests to test both model inputs and outputs</li><li>Effective collaboration, experience in working with Scrum/Agile teams &amp; task tracking</li></ul>
Additional considerations<ul><li>The preferred profile is &quot;all-the-way-rounder&quot; rather than a person with deep expertise in only something specific</li></ul></div>

Fuse Energy

<div>
 Fuse Energy is a forward-thinking renewable energy startup on a mission to deliver a terawatt of renewable energy - fast. We're combining first-principles thinking with cutting-edge technology to build a radically better energy system. We raised $210M from top-tier investors including Multicoin, Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, Box Group and strategic angels like Nico Rosberg, the Co-Founder of Solana and GPs behind Meta, Revolut, Spotify, Uber and more.
 
 
 We're creating a fully integrated energy company: from developing solar, wind and hydrogen projects to real-time power trading and distributed energy installations. By selling directly to consumers, we cut out the middleman, lower costs and pass on savings to customers.
 
 
 But we're not stopping there. We're also building the Energy Network: a decentralised platform of smart devices to electrify our homes, shifting usage to off-peak hours and helping balance the grid. This network strengthens grid stability - a critical foundation for scaling AI data centers and other energy-intensive industries.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Own the reliability, performance, and scalability of Fuse's database infrastructure across Postgres and ClickHouse
 </li>
 <li>
 Build and maintain scalable, reliable data pipelines to support analytics, reporting, and product needs
 </li>
 <li>
 Own the design and evolution of analytical schemas, translating business logic into structured, intuitive data models
 </li>
 <li>
 Migrate and transform data from Postgres into ClickHouse, ensuring performance and reliability
 </li>
 <li>
 Develop and maintain DBT models that reflect our business domain and make data easily accessible for teams
 </li>
 <li>
 Implement tests and data quality checks to ensure reliable and trustworthy datasets
 </li>
 <li>
 Identify and eliminate duplicates, improve data consistency, and enforce clean modelling standards
 </li>
 <li>
 Manage all database and infrastructure changes through IaC &mdash; minimise direct DB modifications
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 3+ years of experience in a backend engineering or data-focused engineering role
 </li>
 <li>
 Writes the cleanest SQL you've ever seen &mdash; proficiency in Python and SQL is non-negotiable
 </li>
 <li>
 Hands-on experience with relational databases, particularly Postgres
 </li>
 <li>
 Experience designing schemas and building data models that reflect real-world business logic
 </li>
 <li>
 Familiarity with DBT or similar data transformation frameworks
 </li>
 <li>
 Strong understanding of data validation, testing, and quality assurance practices
 </li>
 <li>
 Manages all infrastructure through IaC tooling (Pulumi, AWS CDK) &mdash; treats the database as code, not a manual system
 </li>
 <li>
 Grasps new business domains quickly &mdash; able to translate unfamiliar logic into clean, intuitive data models without hand-holding
 
 
 </li>
 </ul>
 
 Bonus
 
 
 
 <ul>
 <li>
 Experience with ClickHouse or columnar databases
 </li>
 <li>
 Familiarity with cloud-based data orchestration tools (Dagster, Step Functions)
 </li>
 <li>
 CI/CD practices for data pipelines and transformations
 </li>
 <li>
 Experience operating databases at scale in a production environment
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 Competitive salary and an equity sign-on bonus
 </li>
 <li>
 Biannual bonus scheme
 </li>
 <li>
 Fully expensed tech to match your needs
 </li>
 <li>
 Paid annual leave
 </li>
 <li>
 Breakfast and dinner allowance for office based employees
 </li>
 </ul>
</div>

Database Reliability Engineer

Explore 308+ Data engineer in Dubai this July. Find roles across top companies and apply now to boost your career.

308 data engineer jobs In Dubai

Data Engineer

Machine Learning Engineer / Data Scientist (Mid-Level)

Data Platform Lead

Senior Analytics Engineer

Data Scientist (Arabic Speaker)

Data Scientist (Arabic Speaker)

Database Reliability Engineer