Senior Associate Data Solutions Engineering
- Hiring from
- United Arab Emirates
- Work type
- Hybrid
- Posted
- Oct 2, 2026
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About Us:
Mubadala is a global and responsible investment company with US$385 billion assets under management. five global offices and business investments in 50+ countries, with the focus of creating sustainable financial returns for the Government of Abu Dhabi.
We have set the ambition to double the size of our portfolio to half a trillion dollars over the next decade. This brings exciting opportunities for people across the organization, enabling them to access new, diverse and challenging experiences.
We invest in our people and give you an unrivalled opportunity for growth, development and success, while contributing to Mubadala's positive impact on local and global communities.
Join us at Mubadala and make change happen!
What you will do:
Data solution architecture
Design end-to-end solutions across source systems, integration services, the enterprise data platform, Snowflake, semantic layers, APIs and business intelligence products.
Translate business outcomes into solution designs, target-state data flows, source-to-target mappings, transformation rules, interface contracts and non-functional requirements.
Define reusable integration patterns for structured, semi-structured and external market or SaaS data, spanning batch, API and event-driven approaches.
Data engineering and platform delivery
Lead, and where required directly contribute to, the design, build and test production ready ETL/ELT pipelines and reusable data services across cloud and hybrid environments.
Review pipeline performance, data latency, throughput, failure patterns and operating cost, and drive practical remediation and optimisation.
Ensure production readiness through automated deployment, version control, environment promotion, rollback planning and runbooks, introducing metadata-driven and configuration-led patterns that reduce manual work.
Analytics, BI and business solution enablement
Own the data-readiness layer for dashboards, executive reporting, operational analytics and AI use cases, ensuring trusted definitions and consistent calculations.
Partner with business teams to define KPIs, validation extracts, dashboard requirements, user personas, refresh frequency, access rules and acceptance criteria.
Challenge unclear or changing requirements and convert them into signed-off requirements, mappings, formulas and controlled revisions, including executive and mobile analytics experiences where security, performance and clarity are critical.
Data quality, governance and security
Embed data-quality checks, reconciliation controls and exception reporting into pipelines and data products, and define reusable data-quality rules with transparent reporting of failures.
Implement role-based security controls and encryption for data at rest and in transit, in line with UAE data privacy regulations and GDPR principles.
Work with governance teams to align data products with the enterprise glossary, catalogue, classification, retention and privacy requirements, and drive resolution of source-data issues through evidence-based analysis and clear ownership.
Delivery leadership and stakeholder management
Lead delivery across multi-disciplinary teams without relying on formal line authority, setting priorities, sequencing dependencies and maintaining clear accountability.
Coordinate with business product owners, investment teams, Human Capital, audit, finance, AI teams, vendors and managed-service partners to deliver agreed outcomes.
Run solution workshops, design reviews, backlog reviews, UAT readiness sessions, issue-resolution calls and go-live checkpoints.
Provide concise, evidence-based status updates covering progress, blockers, decisions, risks and dependencies, balancing tactical delivery needs with long-term platform integrity.
Team enablement, innovation and knowledge transfer
Mentor engineers, analysts and consultants on solution design, data modelling, documentation, testing, troubleshooting and secure delivery practices.
Establish reusable templates, coding standards, design patterns, checklists and code repositories, and review technical outputs before business or production release.
Conduct training sessions and workshops for internal stakeholders, and develop knowledge repositories and best-practice documentation that support reuse and future scaling.
Evaluate emerging technologies, including AI-assisted engineering, serverless ETL, cloud-native orchestration, containerised deployment and observability, where they provide measurable value.
What will you bring:
Experience
A superior platform to grow your career including:
You will operate in a diverse, energetic and forward-thinking environment with hybrid working and wellness benefits to help you grow and develop, and market leading pay and benefits.
Key Indicators:
Location: Abu Dhabi
Flexible Working: Remote working up to 5 days a month.
Mubadala is a global and responsible investment company with US$385 billion assets under management. five global offices and business investments in 50+ countries, with the focus of creating sustainable financial returns for the Government of Abu Dhabi.
We have set the ambition to double the size of our portfolio to half a trillion dollars over the next decade. This brings exciting opportunities for people across the organization, enabling them to access new, diverse and challenging experiences.
We invest in our people and give you an unrivalled opportunity for growth, development and success, while contributing to Mubadala's positive impact on local and global communities.
Join us at Mubadala and make change happen!
What you will do:
Data solution architecture
Design end-to-end solutions across source systems, integration services, the enterprise data platform, Snowflake, semantic layers, APIs and business intelligence products.
Translate business outcomes into solution designs, target-state data flows, source-to-target mappings, transformation rules, interface contracts and non-functional requirements.
Define reusable integration patterns for structured, semi-structured and external market or SaaS data, spanning batch, API and event-driven approaches.
Data engineering and platform delivery
Lead, and where required directly contribute to, the design, build and test production ready ETL/ELT pipelines and reusable data services across cloud and hybrid environments.
Review pipeline performance, data latency, throughput, failure patterns and operating cost, and drive practical remediation and optimisation.
Ensure production readiness through automated deployment, version control, environment promotion, rollback planning and runbooks, introducing metadata-driven and configuration-led patterns that reduce manual work.
Analytics, BI and business solution enablement
Own the data-readiness layer for dashboards, executive reporting, operational analytics and AI use cases, ensuring trusted definitions and consistent calculations.
Partner with business teams to define KPIs, validation extracts, dashboard requirements, user personas, refresh frequency, access rules and acceptance criteria.
Challenge unclear or changing requirements and convert them into signed-off requirements, mappings, formulas and controlled revisions, including executive and mobile analytics experiences where security, performance and clarity are critical.
Data quality, governance and security
Embed data-quality checks, reconciliation controls and exception reporting into pipelines and data products, and define reusable data-quality rules with transparent reporting of failures.
Implement role-based security controls and encryption for data at rest and in transit, in line with UAE data privacy regulations and GDPR principles.
Work with governance teams to align data products with the enterprise glossary, catalogue, classification, retention and privacy requirements, and drive resolution of source-data issues through evidence-based analysis and clear ownership.
Delivery leadership and stakeholder management
Lead delivery across multi-disciplinary teams without relying on formal line authority, setting priorities, sequencing dependencies and maintaining clear accountability.
Coordinate with business product owners, investment teams, Human Capital, audit, finance, AI teams, vendors and managed-service partners to deliver agreed outcomes.
Run solution workshops, design reviews, backlog reviews, UAT readiness sessions, issue-resolution calls and go-live checkpoints.
Provide concise, evidence-based status updates covering progress, blockers, decisions, risks and dependencies, balancing tactical delivery needs with long-term platform integrity.
Team enablement, innovation and knowledge transfer
Mentor engineers, analysts and consultants on solution design, data modelling, documentation, testing, troubleshooting and secure delivery practices.
Establish reusable templates, coding standards, design patterns, checklists and code repositories, and review technical outputs before business or production release.
Conduct training sessions and workshops for internal stakeholders, and develop knowledge repositories and best-practice documentation that support reuse and future scaling.
Evaluate emerging technologies, including AI-assisted engineering, serverless ETL, cloud-native orchestration, containerised deployment and observability, where they provide measurable value.
What will you bring:
Experience
- Minimum 10 years of relevant experience in enterprise data, analytics, integration or solution architecture, including significant hands-on delivery responsibility.
- Proven experience delivering data solutions from requirement definition through design, build, testing, production deployment and support.
- Experience with Snowflake, SQL, data warehouse or lakehouse architecture, ETL/ELT platforms and cloud data services, with strong proficiency in SQL and scripting languages such as Python or Scala.
- Practical experience with Informatica IICS or comparable enterprise integration tooling, alongside DevOps and DataOps practices including Git version control and CI/CD automation (Azure DevOps).
- Hands-on experience with real-time streaming platforms such as Apache Kafka and data integration for hybrid architectures.
- Experience designing secure analytics solutions with Power BI, semantic models, row-level security and controlled production release, with practical exposure to wider BI ecosystems such as Tableau for data readiness checks.
- Experience working with business-critical, confidential or regulated data, applying governance, privacy and access-control requirements.
- Experience coordinating vendors, consultants and cross-functional delivery teams in a complex enterprise environment. Exposure to investment data, Human Capital analytics, enterprise reporting or AI data enablement is highly advantageous.
- Bachelor's degree in Computer Science, Data Engineering, Information Systems or a related quantitative or technical discipline.
- Postgraduate study or certification in cloud data engineering is an advantage.
- Preferred certifications include Microsoft Certified: Azure Data Engineer Associate, and Snowflake, Informatica, Power BI or data architecture certifications relevant to the enterprise stack.
- Data governance, security, TOGAF, ITIL, DevOps or DataOps certification is also valued.
A superior platform to grow your career including:
- A role that has social and financial impact
- Great working environment with talented colleagues
- Market leading pay and benefits including performance pay.
- Hybrid working and wellness benefits to help you live your best work and private life.
- Opportunity to grow and develop through learning and experience.
- Excellent work culture enabled by our values of Accountability, Inspiration, Integrity & Partnership
You will operate in a diverse, energetic and forward-thinking environment with hybrid working and wellness benefits to help you grow and develop, and market leading pay and benefits.
Key Indicators:
Location: Abu Dhabi
Flexible Working: Remote working up to 5 days a month.