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senior data engineer

Lunate

<div>
 
 
 Firm Overview
 
 
 
 
 
 
 Lunate is a new Abu Dhabi-based, Partner-led, independent global alternative investment manager with more than 250 employees and $115 billion of assets under management. Lunate invests across the entire private markets spectrum including buyouts, growth equity, early and late-stage venture capital, private credit, real assets, and public equities and public credit. Lunate aims to be one of the world&rsquo;s leading private markets solutions providers through SMAs and multi-asset class funds, seeking to generate best-in-class risk-adjusted returns for its clients.
 
 
 
 
 
 
 Job Purpose
 
 
 
 
 
 
 The Senior Data Engineer will be the first dedicated internal data engineering hire in Lunate&rsquo;s Data &amp; AI function. This role is responsible for building dependable ingestion and transformation pipelines into Snowflake, shaping high-quality, well-modelled datasets that power reporting, operations, and AI-enabled products. You will work closely with the Head of Data &amp; AI and partner with Infrastructure (who own Snowflake account and platform setup) to deliver a modern, data-as-code engineering practice with strong controls, testing, and repeatability, supporting both BI and AI/Agentic workloads.
 
 
 
 
 
 
 Key Duties and Responsibilities
 
 
 
 
 
 <ul>
 <li>
 Build and own ingestion pipelines into Snowflake using modern ELT patterns (Fivetran or equivalent, plus custom ingestion where needed), handling schema drift and source changes safely.
 </li>
 <li>
 Leverage AI Tools to design and automate our pipelines.
 </li>
 <li>
 Implement a layered data architecture (raw, standardised, business) that preserves immutability, auditability, and supports reprocessing and backfills.
 </li>
 <li>
 Develop transformations as version-controlled code (SQL and Python) using dbt or equivalent tooling.
 </li>
 <li>
 Apply pragmatic data modelling practices, using dimensional (Kimball) or relational approaches where appropriate.
 </li>
 <li>
 Build data quality and reconciliation into pipelines, with automated checks and visible quality signals.
 </li>
 <li>
 Operate pipelines like software: CI/CD, automated testing, peer review, and controlled promotion across environments.
 </li>
 <li>
 Optimise Snowflake usage for performance and cost, working with Infrastructure on governance controls.
 </li>
 <li>
 Partner with BI practitioners and AI engineers to deliver AI-ready datasets with consistent semantics and clear lineage.
 </li>
 <li>
 Collaborate with investment, operations, and finance teams to translate requirements into robust data products.
 </li>
 <li>
 Contribute to engineering standards, patterns, and documentation as the data function scales.
 </li>
 </ul>
 
 
 
 
 
 Qualifications and Experience
 
 
 
 
 
 <ul>
 <li>
 6+ years of professional data engineering experience delivering production pipelines.
 </li>
 <li>
 Strong experience with Snowflake&rsquo;s full suite of products &ndash; especially core functionality.
 </li>
 <li>
 Hands-on experience with dbt, including testing and environment management.
 </li>
 <li>
 Familiarity with modern ingestion tools such as Fivetran.
 </li>
 <li>
 Strong grounding in data modelling fundamentals (Kimball and relational).
 </li>
 <li>
 Python-native, comfortable writing production-quality pipeline and orchestration code.
 </li>
 <li>
 Strong software engineering discipline applied to data (Git, CI/CD, automated testing).
 </li>
 <li>
 Experience building replayable, idempotent pipelines with backfill support.
 </li>
 <li>
 Financial services experience preferred, with understanding of audit, restatement, and as-of data concepts.
 </li>
 </ul>
</div>

Senior Data Engineer

TALENTMATE

<div>
 
 Job Description
 
 
 
 
 Job Description
 
 
 
 
 Overview
 
 
 
 
 About Presight
 
 
 
 Presight is an ADX-listed public company with Abu Dhabi based G42 as its majority shareholder and is the region&rsquo;s leading big data analytics company powered by GenAI. It combines big data, analytics, and AI expertise to serve every sector, of every scale, to create business and positive societal impact. Presight excels at all-source data interpretation to support insight-driven decision-making that shapes policy and creates safer, healthier, happier, and more sustainable societies. Today, through its range of GenAI-driven products and solutions, Presight is bringing Applied AI to the private and public sector, enabling them to realize their AI strategy and ambitions faster.
 
 
 
 The Opportunity
 
 
 
 Presight is looking for an astute, proficient and qualified Senior Data Engineer to assess, analyze and work with data concepts, use-cases &amp; complex new data sources to provide business insights to customers and support the implementation &amp; integration of the data sources into the Presight platform.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Solve challenging problems, using python coding skills.
 </li>
 <li>
 Design, build and launch new data extraction, transformation &amp; loading processes in production.
 </li>
 <li>
 Web crawling, data cleaning, data annotation, data ingestion and data processing.
 </li>
 <li>
 Reading and collating complex data sets.
 </li>
 <li>
 Creating and maintaining data pipelines.
 </li>
 <li>
 Continual focus on process improvement to drive efficiency and productivity within the team.
 </li>
 <li>
 Use of Python, SQL, ES, Shell etc. to build the infrastructure required for optimal extraction, transformation, and loading of data.
 </li>
 <li>
 Provide insights into key business performance metrics by building analytical tools that utilize the data pipeline.
 </li>
 <li>
 Support the wider business with their data needs on an ad hoc basis.
 </li>
 <li>
 Comply with QHSE (Quality Health Safety and Environment), Business Continuity, Information Security, Privacy, Risk, Compliance Management and Governance of Organizations policies, procedures, plans and related risk assessments.
 
 
 </li>
 </ul>
 
 Qualifications:
 
 
 
 <ul>
 <li>
 Bachelor's degree in computer engineering, Computer Science, or Electrical Engineering and Computer Sciences.
 </li>
 <li>
 6+ years of programming experience, solid coding skills in Python, Shell, and Java
 </li>
 <li>
 Good corporate capacity, good communication skills.
 </li>
 <li>
 Experience with Web crawling, cleaning.
 </li>
 <li>
 Experience with solution architecture, data ingestion, query optimization, data segregation, ETL, ELT, AWS, EC2, S3, SQS, lambda, Elastic Search, Redshift, CI/CD frameworks and workflows.
 </li>
 <li>
 Working knowledge of data platform concepts - data lake, data warehouse, ETL, big data processing (designing and supporting variety/velocity/volume), real time processing architecture for data platforms, scheduling and monitoring of ETL/ELT jobs
 </li>
 <li>
 PostgreSQL and programming (preferably Java, Python), proficiency in understanding data, entity relationships, structured &amp; unstructured data, SQL and NoSQL databases
 </li>
 <li>
 Knowledge of best practice in optimizing columnar and distributed data processing system and infrastructure
 </li>
 <li>
 Experienced in designing and implementing dimensional modelling
 </li>
 <li>
 Knowledge of machine learning and data mining techniques in one or more areas of statistical modelling, text mining and information retrieval.
 
 
 </li>
 </ul>
 Job Details
 
 
 Role Level: Not Applicable Work Type: Full-Time Country: United Arab Emirates City: Dubai Company Website: https://www.presight.ai Job Function: Data Science &amp; AI Company Industry/
 
 
 Sector: Other
 
 
 What We Offer
 
 
 
 About The Company
 
 
 
 Searching, interviewing and hiring are all part of the professional life. The TALENTMATE Portal idea is to fill and help professionals doing one of them by bringing together the requisites under One Roof. Whether you're hunting for your Next Job Opportunity or Looking for Potential Employers, we're here to lend you a Helping Hand.
 
 
 Report
 
 
 Disclaimer: talentmate.com is only a platform to bring jobseekers &amp; employers together. Applicants are advised to research the bonafides of the prospective employer independently. We do NOT endorse any requests for money payments and strictly advice against sharing personal or bank related information. We also recommend you visit Security Advice for more information. If you suspect any fraud or malpractice, email us at abuse@talentmate.com.
</div>

Deriv.com

<div><h3 class="jobSectionHeader">Job Information</h3>
<ul><li>Job Opening ID ZR_2195_JOB
</li><li>Industry Business Intelligence
</li><li>Date Opened 22/06/2026
</li><li>Job Type Full time
</li><li>City Dubai
</li><li>Province -
</li><li>Country United Arab Emirates
</li><li>Postal Code -</li></ul></div>
 <div><h3 class="jobSectionHeader">Job Description</h3>
<div><div>Data pipelines don&rsquo;t fail in staging. They fail at 3 a.m. on month-end, when compliance needs the numbers and the dashboard is showing yesterday&rsquo;s data. You&rsquo;ll build the pipelines that don&rsquo;t break&mdash;and when they do, you&rsquo;ll know before anyone else does. 
 
</div><div></div> 
<div>This isn&rsquo;t a role where you maintain someone else&rsquo;s SQL. You&rsquo;ll build data infrastructure that powers trading decisions, product analytics, compliance, and AI/ML systems across a global fintech. You&rsquo;ll own data accuracy end-to-end, raise the engineering bar for the team, and catch problems before they reach your stakeholders. 
 
</div> 
 
<div>Why This Matters 
 
</div><div></div> 
<div>Deriv&rsquo;s mission is Trading for Anyone, Anywhere, Anytime. Millions of traders, around the clock, across regulatory regimes. Every trade generates data. Every data point feeds analytics, compliance checks, fraud detection, and AI systems that serve customers in real time. 
 
</div><div></div> 
<div>When a pipeline delivers stale data, a trader sees the wrong price. When a schema drifts undetected, a compliance report goes wrong. When governance is an afterthought, regulators ask questions nobody can answer. Data engineering at Deriv isn&rsquo;t back-office plumbing. It&rsquo;s the infrastructure that the entire business trusts. 
 
</div> 
 
<div>Why Deriv 
 
</div><div></div> 
<div>We&rsquo;re in production, not planning.
 
</div><ul><li>Natural language interfaces querying the data warehouse directly&mdash;leaders ask questions in English, answers come back in seconds
 
</li><li>Continuous KPI monitoring with anomaly detection surfacing problems before stakeholders notice
 
</li><li>Dozens of fraud detection models running against production data, continuously
 
</li><li>400+ users on our internal workflow orchestration platform, fed by the data infrastructure you&rsquo;ll help build and scale
 
</li></ul><div>We share openly. Deriv ed is where we write about what we&rsquo;re shipping, what breaks, and what we figured out the hard way. You&rsquo;ll join a transformation that&rsquo;s underway, not one waiting for approval. 
 
</div> 
 
<div>What You&rsquo;ll Do 
 
</div><div></div> 
<div>Your work cuts across trading and product analytics, compliance and regulatory reporting, AI/ML feature pipelines, and business intelligence. Your placement depends on team needs and your strengths&mdash;your impact won&rsquo;t be limited to one domain. 
 
</div><div></div> 
<div>Build pipelines that are governed by design
 
</div><ul><li>Design and build ETL/ELT pipelines across batch and real-time workloads using AI-assisted development&mdash;reducing build time without cutting reliability
 
</li><li>Bake in observability from the start: freshness checks, completeness monitoring, schema drift detection, lineage tracking, and alerting. Not retrofitted after launch
 
</li>Implement automated data quality checks and anomaly detection into every pipeline&mdash;governance built in, not bolted on 
<li>
 
</li></ul><div></div> 
<div>Own data accuracy before anyone has to ask
 
</div><ul><li>Identify and resolve data issues before they surface to analysts or stakeholders
 
</li><li>Define and maintain data contracts: SLAs, SLOs, schema agreements, and producer-consumer alignment
 
</li>Handle PII, access control, and auditability correctly in a regulated financial environment 
<li>
 
</li></ul><div></div> 
<div>Make the platform better than you found it
 
</div><ul><li>Optimise warehouse performance and cost&mdash;query efficiency, partitioning, clustering, orchestration reliability
 
</li><li>Build data models designed to scale beyond the immediate use case: dimensional modelling, semantic layers, reusable abstractions
 
</li>Spot gaps in the data platform and address them without waiting to be assigned 
<li>
 
</li></ul><div></div> 
<div>Raise the bar for the team
 
</div><ul><li>Partner with analysts, product, finance, and compliance teams to translate requirements into reliable, governed data products
 
</li><li>Peer-review pipeline code and push quality standards higher across the team
 
</li>Help onboard new engineers&mdash;share context, catch mistakes early, make others productive faster 
<li>
 
 
</li></ul> 
<div>Who You Are 
 
</div><div></div> 
<div>You build pipelines, not just queries
 
</div>6+ years in data engineering. You know that writing SQL is the easy part. The hard part is making sure data arrives on time, matches the schema you promised, and doesn&rsquo;t silently break when upstream changes. You think about data quality before someone files a bug. 
<ul><li>
 
</li></ul><div></div> 
<div>You know the cloud data stack cold
 
</div>GCP, BigQuery, Airflow, Python&mdash;or the equivalent at comparable scale. You&rsquo;ve built and maintained real pipelines across batch and streaming workloads. You&rsquo;ve shipped with dbt or Dataform and understand why transformation layers matter. You use AI coding assistants daily as part of your workflow, not as a novelty. 
<ul><li>
 
</li></ul><div></div> 
<div>You think in contracts, not assumptions
 
</div>Data modelling techniques like Kimball star schema, Data Vault, or Medallion architecture aren&rsquo;t buzzwords to you&mdash;they&rsquo;re tools you pick based on the problem. You understand that a pipeline without a data contract is a pipeline waiting to fail. Even better if you&rsquo;ve implemented data contract frameworks or schema registries at scale. 
<ul><li>
 
</li></ul><div></div> 
<div>You fix root causes, not symptoms
 
</div>When data is wrong, you don&rsquo;t patch the dashboard. You trace the problem to its source, fix it systematically, and make sure it doesn&rsquo;t recur. You explain what happened clearly&mdash;to engineers and to non-technical stakeholders who need to trust the numbers again. 
<ul><li>
 
</li></ul><div></div> 
<div>You make the people around you better
 
</div>You share learnings actively, create reusable resources, and give feedback that helps others ship better code. When a junior engineer is stuck, you unblock them. When a stakeholder&rsquo;s requirements are vague, you ask the right questions and turn ambiguity into a spec. 
<ul><li>
 
</li></ul><div></div> 
<div>You&rsquo;ve seen what regulated data looks like
 
</div>A fintech, trading, or compliance-heavy background is a strong plus. You know the difference between handling PII in a textbook and handling it when auditors are checking your work. Experience with warehouse cost optimisation and containerised data platforms rounds out the picture. 
<ul><li>
 
 
</li></ul> 
<div>Tech Stack
 
</div><ul><li>Cloud &amp; Warehouse: GCP, BigQuery
 
</li><li>Orchestration: Airflow
 
</li><li>Languages: Python, SQL
 
</li><li>Transformation: dbt / Dataform
 
</li><li>Streaming: Kafka, Pub/Sub
 
</li>Practices: CI/CD, version-controlled pipelines, peer review, AI-assisted development 
<li>
 
</li></ul> 
<div>The Honest Reality 
 
</div><div></div> 
<div>This is demanding work. You&rsquo;ll own pipeline reliability in a business where stale data means wrong trading decisions and missed compliance deadlines. You&rsquo;ll debug schema mismatches at month-end when nobody can wait until Monday. You&rsquo;ll push for governance practices when it&rsquo;s easier to just ship the quick fix. 
 
</div><div></div> 
<div>But you&rsquo;ll build infrastructure the entire company depends on. You&rsquo;ll see your pipelines powering dashboards, feeding AI models, and passing compliance audits. And you&rsquo;ll work with a team that treats data engineering as a craft, not a cost centre. 
 
</div><div></div> 
<div>If you want predictable work and clean datasets handed to you, this isn&rsquo;t it. If you want to build data systems that actually matter, it might be.</div></div></div>

amana

<div>
 
 
 Role Summary:
 
 
 
 
 
 
 We are seeking a highly skilled Senior Python Data Engineer to join our Data &amp; Analytics team. This role is focused on designing, building, and maintaining enterprise-grade data pipelines, integrations, data warehouse solutions, and reporting datasets that support operational reporting, business intelligence, analytics, and decision-making across the organization. The ideal candidate combines strong software engineering practices with deep data engineering expertise and is comfortable working across the full data lifecycle, from source system integration and ETL development to data warehousing and reporting enablement
 
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 
 
 
 Data Engineering &amp; Integration:
 
 
 <ul>
 <li>
 Design, develop, and maintain scalable ETL/ELT pipelines using Python.
 </li>
 <li>
 Build integrations with a variety of data sources including APIs, relational databases, flat files, and third-party systems.
 </li>
 <li>
 Implement data extraction, transformation, validation, and loading processes. Develop incremental loading and change-tracking mechanisms.
 </li>
 <li>
 Troubleshoot, optimize, and enhance existing data pipelines.
 </li>
 </ul>
 
 
 
 
 
 Data Platform Development
 
 :
 
 <ul>
 <li>
 Develop reusable and maintainable data processing components.
 </li>
 <li>
 Build and enhance internal data integration and orchestration capabilities.
 </li>
 <li>
 Participate in solution design, architecture reviews, and technical discussions.
 </li>
 <li>
 Produce well-structured, testable, and documented code. Contribute to engineering standards and best practices.
 </li>
 </ul>
 
 
 
 
 
 Workflow Orchestration
 
 
 <ul>
 <li>
 Design and implement Apache Airflow DAGs.
 </li>
 <li>
 Build reliable workflow orchestration and scheduling processes.
 </li>
 <li>
 Monitor pipeline execution and resolve operational issues.
 </li>
 <li>
 Improve observability, reliability, and performance of data workflows.
 </li>
 </ul>
 
 
 
 
 
 Data Warehousing &amp; Reporting
 
 
 <ul>
 <li>
 Design, build, and maintain data warehouse structures that support reporting and analytics requirements.
 </li>
 <li>
 Develop reporting-ready datasets and data models.
 </li>
 <li>
 Optimize SQL queries and warehouse performance.
 </li>
 <li>
 Support the delivery of operational, management, and analytical reporting requirements.
 </li>
 <li>
 Collaborate with business stakeholders, analysts, and reporting teams to ensure data accuracy and usability.
 </li>
 <li>
 Assist in troubleshooting reporting and data quality issues when required
 </li>
 </ul>
 
 
 
 
 
 Engineering Excellence
 
 
 <ul>
 <li>
 Build and maintain Docker images and containerized applications.
 </li>
 <li>
 Participate in code reviews and technical knowledge sharing.
 </li>
 <li>
 Develop unit tests and integration tests.
 </li>
 <li>
 Utilize Git-based development workflows and version control best practices.
 </li>
 <li>
 Support CI/CD and deployment processes where required
 </li>
 </ul>
 
 
 
 
 
 Requirements:
 
 
 
 - Has 5+ years of experience, good understanding of Python, Apache Airflow &ndash; Power BI &ndash; APIs (Rest API) and database
 
 
 - Candidates should already be based in the UAE
 
 
 - Strong influencing, leadership, and communication skills with the ability to operate effectively across both technical and non-technical audiences
 
 
 - Excellent attention to detail, problem-solving, and analytical skills.
 
 
 - Strong communication skills and ability to work effectively in a remote environment.
 
 
 
 
 
 
 Preferred Qualifications:
 
 
 
 Good understanding of the stock market, database systems with an understanding of trading systems, MT Platforms (MT4, MT5) and accounts.
 
</div>

Senior Python Data Engineer

DICETEK LLC

<div>Role Summary
The Senior Engineer &ndash; Data Governance &amp; Platform Lead (IB&amp;M) is a hands-on senior technical role responsible for defining, implementing, and governing the IB&amp;M Data Platform with a strong focus on data governance, quality, lineage, security, and platform standards.
The role will work closely with Global Markets, Investment Banking, Risk, Compliance, and Analytics teams to ensure data is trusted, compliant, and scalable across the enterprise. This is not a people‑management role but requires strong technical leadership and ownership across the data lifecycle.
Key Responsibilities<ul><li>
Define and govern the IB&amp;M Data Platform, ensuring strong data governance, quality, lineage, security, and compliance.
</li><li>Lead the design and implementation of scalable data platform standards across Azure Lakehouse (ADLS, Databricks, Delta Lake).
</li><li>Provide technical leadership on data architecture, platform engineering, and governance best practices.
</li><li>Collaborate with Global Markets, Risk, Compliance, Analytics, and engineering teams to deliver trusted and compliant data solutions.
</li><li>Review solution designs, establish platform standards, and ensure scalability, performance, security, and regulatory compliance.</li></ul> 
Experience<ul><li>10+ years of experience in Data Engineering, Data Platforms, or Data Architecture</li><li>Proven experience leading data governance initiatives in large, regulated environments (Banking / Financial Services preferred)</li><li>Strong background supporting Global Markets / Investment Banking data domains is highly desirable</li></ul>
Technical Skills<ul><li>Strong hands-on experience with:
</li></ul>o Azure Data Lake (ADLS)
o Databricks / Delta Lake / Lakehouse architectures
o Data quality, schema enforcement, and validation frameworks<ul><li>Experience with data cataloging and governance tools (e.g., Unity Catalog, Informatica Axon or similar)
</li><li>Solid understanding of:
</li></ul>o Data modeling (analytical and canonical models)
o Metadata management and lineage
o Secure data access and entitlements<ul><li>Good understanding of AI/ML and analytics enablement within governed data platforms</li></ul>
Soft Skills<ul><li>Strong ownership mindset with ability to work independently</li><li>Excellent stakeholder management and communication skills</li><li>Ability to translate regulatory and business requirements into technical solutions</li><li>Comfortable working in complex, multi‑vendor, enterprise environments</li></ul></div>

Data Governance & Platform Lead – IB&M

ENEC Operations

<div>
 
 The Data and AI Engineering Expert is a senior hands-on technical authority responsible for the design, development, and operationalization of enterprise data and AI platforms across ENEC. This role leads the engineering delivery of scalable, secure, and compliant data pipelines, AI/ML solutions, and analytics platforms leveraging technologies such as Databricks (Delta Lake, Unity Catalog, MLflow, Delta Live Tables), Microsoft Azure (Azure Data Factory, Azure ML, Microsoft Fabric, Azure AI Foundry, Copilot Studio), Collibra (Data Governance &amp; Data Quality), Power BI, and OT/industrial data systems including PI System, SCADA, and DCS.
 
 
 
 
 
 The Expert applies deep engineering expertise to architect and deliver production-grade solutions, ensures data governance and quality standards are upheld, and drives the adoption of AI and analytics capabilities that directly support ENEC's mission of safe, innovative, and efficient nuclear energy generation. This role acts as a principal technical contributor and mentor, enabling operational excellence and digital transformation at scale.
 
 
 Activity: Data Engineering Architecture &amp; Platform Development
 
 
 
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Design, build, and maintain scalable, secure, and high-performance data platforms including Lakehouse architectures using Databricks Delta Lake, Unity Catalog, and Delta Live Tables (DLT).
 
 
 &bull; Develop and operationalize robust data pipelines, ETL/ELT workflows, and integration frameworks using Azure Data Factory, Databricks Workflows, and related orchestration tools.
 
 
 &bull; Architect and implement data models, semantic layers, and data products that serve enterprise analytics, AI, and reporting needs.
 
 
 &bull; Ensure seamless integration of OT and industrial data sources &mdash; including PI System, SCADA, and DCS &mdash; into enterprise data platforms.
 
 
 &bull; Design and implement APIs, data contracts, and integration frameworks to enable enterprise-wide data consumption.
 
 
 &bull; Ensure platform scalability, resilience, high availability, and disaster recovery capabilities in compliance with nuclear and regulatory requirements.
 
 
 &bull; Apply and enforce data standards, naming conventions, and metadata management practices across all data assets using Collibra and Unity Catalog.
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Design, develop, and deploy production-grade machine learning, deep learning, and generative AI models using Azure ML, MLflow, and Databricks ML.
 
 
 &bull; Engineer end-to-end MLOps pipelines covering model training, versioning, validation, deployment, monitoring, and retraining &mdash; ensuring reliability and reproducibility.
 
 
 &bull; Build and operationalize AI-powered solutions including predictive analytics, anomaly detection, natural language processing (NLP), and GenAI/LLM-based applications using Azure AI Foundry and Copilot Studio.
 
 
 &bull; Develop BI and semantic models in Microsoft Fabric and Power BI, enabling self-service analytics and executive reporting across the organization.
 
 
 &bull; Apply Responsible AI principles and governance frameworks to all AI and ML solutions, ensuring explainability, fairness, and compliance.
 
 
 &bull; Conduct rigorous model evaluation, performance benchmarking, and validation to ensure solutions meet accuracy, reliability, and safety standards.
 
 
 &bull; Contribute to the continuous improvement of AI engineering standards, patterns, and reusable components across the enterprise.
 
 
 Activity: Advanced Subject Matter Knowledge
 
 
 
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Demonstrates deep, hands-on expertise in enterprise data engineering, AI/ML platform development, and cloud-native architectures within highly regulated environments.
 
 
 &bull; Maintains current knowledge of global trends in data engineering, MLOps, GenAI, cloud technologies (Azure, hybrid, on-premise), and nuclear industry compliance requirements.
 
 
 &bull; Understands the full lifecycle of data and AI platforms including design, development, testing, deployment, monitoring, and decommissioning.
 
 
 &bull; Applies comprehensive knowledge of data governance frameworks (Collibra, Unity Catalog), master data management, data quality, and lineage management.
 
 
 &bull; Possesses strong awareness of OT/IT convergence, industrial data systems (PI System, SCADA, DCS), and their integration into enterprise analytics environments.
 
 
 &bull; Maintains expert-level proficiency in programming languages and frameworks including Python, SQL, Spark, and relevant AI/ML libraries.
 
 
 Activity: Complex Problem Solving &amp; Innovation
 
 
 
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Tackles complex, ambiguous engineering challenges in data platform architecture, AI model development, and system integration &mdash; delivering innovative, compliant, and production-ready solutions.
 
 
 &bull; Leads root cause analysis and corrective/preventive actions for platform incidents, data quality failures, model degradation, and system disruptions.
 
 
 &bull; Develops and implements robust engineering solutions to address performance bottlenecks, scalability constraints, and integration challenges.
 
 
 &bull; Navigates conflicting technical requirements, evolving regulatory standards, and stakeholder needs to deliver optimal engineering outcomes.
 
 
 &bull; Drives continuous improvement by benchmarking against global engineering best practices, evaluating emerging technologies, and implementing lessons learned.
 
 
 &bull; Leads proof-of-concept and pilot initiatives to evaluate new data and AI technologies and engineering approaches
 
 
 
 
 
 Activity: Applied Skills &amp; Professional Know-How
 
 
 
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Expertly engineers, deploys, and operates scalable, secure, and compliant data and AI platforms across Databricks, Azure, and OT environments.
 
 
 &bull; Applies hands-on proficiency in building data pipelines, ML models, GenAI solutions, BI semantic models, and governance frameworks in production environments.
 
 
 &bull; Mentors and develops junior and mid-level data engineers, data scientists, and analytics engineers &mdash; building future-ready technical capabilities.
 
 
 &bull; Leads technical design reviews, code reviews, and architecture assessments to uphold engineering quality and best practices.
 
 
 &bull; Effectively translates complex technical concepts into clear, actionable insights for both technical and non-technical stakeholders.
 
 
 &bull; Documents solutions, engineering patterns, and technical standards to build institutional knowledge and enable knowledge transfer.
 
 
 Activity: Security, Governance &amp; Compliance
 
 
 
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Design and enforce data security, access control, and privacy frameworks across all data and AI platforms using Unity Catalog, Collibra, and Azure security controls.
 
 
 &bull; Ensure all data engineering and AI solutions comply with national and international nuclear regulations, FANR requirements, and Responsible AI principles.
 
 
 &bull; Maintain comprehensive data lineage, audit trails, and documentation to support regulatory, audit, and governance requirements.
 
 
 &bull; Implement and enforce data quality frameworks and data governance policies using Collibra Data Quality and Unity Catalog.
 
 
 &bull; Conduct regular platform security assessments, data quality audits, and compliance reviews.
 
 
 &bull; Oversee risk management, audit readiness, and the implementation of robust technical controls for all platform operations.
 
 
 
 
 
 
 
 
 
 Minimum
 
 
 
 &bull; Bachelor&rsquo;s degree in computer science, Information Technology, Data Management, Engineering, or related discipline.
 
 
 &bull; Minimum 12+ years' hands-on experience in enterprise data engineering, AI/ML platform development, and cloud-native architectures, including production deployment and operations.
 
 
 &bull; Experience embedding governance within modern data platforms (preferably Databricks) and integrating SAP/Oracle ERP domains.
 
 
 
 
 
 
 
 
 
 Preferred
 
 
 
 
 
 
 &bull; Master&rsquo;s degree in a relevant field.
 
 
 &bull; Experience in energy, utilities, nuclear, financial services, government, or other highly regulated sectors.
 
 
 &bull; Demonstrated AI governance experience (provenance, bias monitoring, model data requirements) in data bricks or similar AI/analytics platforms exposure.
 
 
 &bull; Demonstrated experience leading large-scale data and AI engineering programs
 
 
 
 
 
 
 
 
 
 Certification -
 
 
 
 
 
 
 Multiple cloud and AI certifications. Microsoft Fabric, Azure AI Foundry, or Databricks Unity Catalog specialty certifications. Industry publications or contributions in data engineering or AI.
 
 
 
 
 
 Relevant certifications in one or more of: Databricks (Data Engineer Associate/Professional, ML Professional), Microsoft Azure (Data Engineer, AI Engineer, Solutions Architect), MLOps, or Data Governance (Collibra).
 
</div>

Data and AI Engineering Expert

China Civil Engineering Construction Corporation

Career Opportunities &ndash; Dubai RTA Infrastructure Project(CCECC) is expanding its project team in Dubai and is hiring experienced professionals for a high-profile Roads &amp; Transport Authority (RTA) infrastructure project.The project includes major roadworks, bridges, underpasses, flyovers, and multi-utility networks.Project Management / Construction<ul><li>Project Manager (1)</li><li>Construction Manager &ndash; Utilities (1)</li><li>Construction Manager &ndash; Structures (1)</li><li>Construction Manager &ndash; Roads (1)</li><li>Project Engineer &ndash; Utilities (2)</li><li>Project Engineer &ndash; Structures (2)</li><li>Project Engineer &ndash; Roads (2)</li><li>Site Engineer &ndash; Utilities (4)</li><li>Site Engineer &ndash; Structures (4)</li><li>Site Engineer &ndash; Roads (4)</li></ul>Engineering / Technical<ul><li>Senior Technical Engineer (2)</li><li>Technical Engineer (3)</li><li>Design Coordinator (1)</li><li>Assistant Technical Engineer (1)</li></ul>Planning<ul><li>Senior Planning Engineer (1)</li><li>Planning Engineer (2)</li></ul>Commercial &amp; Contracts<ul><li>Contracts Manager (1)</li><li>Assistant Contracts Manager (1)</li><li>Quantity Surveyor (3)</li><li>Senior Quantity Surveyor (2)</li></ul>Utilities &amp; NOC<ul><li>Senior Utility Engineer (2)</li><li>Utility Engineer (4)</li><li>NOC Coordinator (2)</li><li>Stakeholder Coordinator (2)</li></ul>QA/QC &amp; Material<ul><li>Senior QA/QC Engineer (1)</li><li>QA/QC Engineer (2)</li><li>QA/QC Inspector (4)</li><li>Material Engineer (1)</li><li>Lab Technician (4)</li></ul>HSE &amp; Traffic Management<ul><li>HSE Manager (1)</li><li>Senior HSE Engineer (2)</li><li>HSE Officer (3)</li><li>Traffic Management Engineer (TTM) (1)</li><li>Traffic Management Supervisor (1)</li></ul>Survey<ul><li>Chief Surveyor (2)</li><li>Land Surveyor (3)</li></ul>Drafting / BIM<ul><li>Senior Draughtsman (2)</li><li>Draughtsman &ndash; Roads (3)</li><li>Draughtsman &ndash; Utilities &amp; NOC (3)</li><li>Draughtsman &ndash; Structures (2)</li><li>Draughtsman &ndash; TTM (2)</li></ul>Plant / Logistics / Support<ul><li>Machinery Coordinator (2)</li><li>Storekeeper (2)</li><li>Document Controller (2)</li><li>Lifting Appointed Supervisor (3)</li></ul>Apply here and also send your Application Details toEmail: libin.kurian@cceccdubai.com Subject Line: Mention the position applied forOnly relevant profiles with UAE project experience will be considered.CANDIDATES WITHOUT UAE EXPERIENCE SHOULD NOT APPLYPay: AED10,000.00 - AED45,000.00 per monthApplication Question(s):<ul><li>What is your Notice Period ?</li><li>Do you have Dubai RTA experience ?</li><li>What is your Current actual salary + Benefits if any ?</li><li>What is your Current Location ?</li><li>Please share your contact number.</li><li>what is your current visa status ?</li></ul>Work Location: In person

Hiring for Dubai RTA Project (Infrastructure)

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Data and AI Engineering Expert

Hiring for Dubai RTA Project (Infrastructure)