data scientist

devops engineer

ai engineer

estimation engineer

senior ai engineer

data engineer

HTC Global Services

<div>
 
 Job Description
 
 
 
 
 About the Role:
 
 
 
 We are seeking a Data Engineer (Innovation) with 6+ years of experience to design, develop and maintain data pipelines to support AI initiatives.
 
 
 
 Requirements
 
 
 
 <ul>
 <li>
 Collaborate with data scientists to understand requirements and ensure data availability and quality.
 </li>
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 Implement data processing and transformation logic to prepare data for analysis and modelling.
 </li>
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 Monitor and optimize data pipelines for performance, scalability, and reliability.
 </li>
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 Stay abreast of the latest advancements in data engineering technologies and best practices.
 </li>
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 Contribute to low-level architecture/technical design aligned to the high-level solution and business
 </li>
 <li>
 requirements
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 Work within the agile development team to analyse and decompose stories into tasks for simpler
 </li>
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 implementation
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 Proactively identify new frameworks/tools/processes to enhance the efficiency of the development team
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 Responsible for the end-to-end quality of your own deliverables
 </li>
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 Communicate clearly and effectively with team members throughout all the implementation lifecycle
 
 
 </li>
 </ul>
 
 Experience
 
 
 
 <ul>
 <li>
 Bachelor's degree or higher in Computer Science, Engineering, or a related field.
 </li>
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 Proven experience working as a Data Engineer or similar role, preferably in the airline industry or a related field.
 </li>
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 Proficiency in programming languages such as Python, Java, or Scala, as well as experience with data processing frameworks (e.g., Apache Spark).
 </li>
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 Strong understanding of database technologies and SQL.
 </li>
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 Experience with cloud platforms and services (e.g., AWS, Azure, Google Cloud) is a plus.
 
 
 </li>
 </ul>
</div>

Data Engineer (Innovation)

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>
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 Build data quality and reconciliation into pipelines, with automated checks and visible quality signals.
 </li>
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 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>
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 Hands-on experience with dbt, including testing and environment management.
 </li>
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 Familiarity with modern ingestion tools such as Fivetran.
 </li>
 <li>
 Strong grounding in data modelling fundamentals (Kimball and relational).
 </li>
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 Python-native, comfortable writing production-quality pipeline and orchestration code.
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 Strong software engineering discipline applied to data (Git, CI/CD, automated testing).
 </li>
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 Experience building replayable, idempotent pipelines with backfill support.
 </li>
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 Financial services experience preferred, with understanding of audit, restatement, and as-of data concepts.
 </li>
 </ul>
</div>

Senior Data Engineer

DICETEK LLC

<div>We are looking for a skilled Data Engineer specializing in Data Cleansing &amp; Quality (DQ) to join our dynamic team. As a Data Engineer, you will be responsible for ensuring the accuracy, consistency, and reliability of our data assets through various data cleansing techniques and quality assessments.<h3 class="jobSectionHeader">
Key Responsibilities:</h3><ul><li>
Utilize Python Notebooks, SSIS, Fabric Builds / Power BI, and other data engineering tools to cleanse and transform data.</li><li>
Develop and implement data quality processes to monitor and improve the integrity of our data.</li><li>
Collaborate with cross-functional teams to define data quality standards and best practices.</li><li>
Optimize data cleansing pipelines for efficiency and scalability.</li></ul><h3 class="jobSectionHeader">
Qualifications:</h3><ul><li>
Proven experience in data engineering, specifically in data cleansing and quality assurance.</li><li>
Proficiency in Python Notebooks, SSIS, Fabric Builds / Power BI, and equivalent data engineering tools.</li><li>
Strong understanding of data quality principles and best practices.</li><li>
Excellent problem-solving skills and attention to detail.</li><li>
Ability to work both independently and collaboratively in a fast-paced environment.</li></ul></div>

Data Engineer- Data Cleansing & Quality (DQ)

Birbal AI

<div>
 
 The Data Engineer will be responsible for supporting data management, system integration, reporting data flows, and enterprise application data activities. The role requires hands-on experience in SQL, data pipelines, data extraction, transformation, APIs, CRM/Dataverse data structures, reporting datasets, and production support.
 
 
 
 
 
 Key Responsibilities
 
 
 Develop, maintain, and optimize data pipelines and data integration workflows.
 
 
 Work with SQL databases, CRM/Dataverse, APIs, and enterprise application data sources.
 
 
 Support data extraction, transformation, loading, and reconciliation activities.
 
 
 Build and maintain datasets for dashboards, reports, and analytics.
 
 
 Troubleshoot data issues related to missing records, incorrect mappings, failed integrations, or report mismatches.
 
 
 Support integration between enterprise applications, portals, CRM systems, and reporting platforms.
 
 
 Work with Power BI datasets, SQL scripts, views, stored procedures, and data models.
 
 
 Support automation workflows using Power Automate or similar platforms.
 
 
 Coordinate with business users, application teams, QA teams, and data quality resources to resolve data issues.
 
 
 Prepare and maintain technical documentation for data flows, mappings, APIs, and transformation logic.
 
 
 Ensure data security, confidentiality, governance, and compliance requirements are followed.
 
 
 
 
 
 Required Skills
 
 
 Strong SQL development and database knowledge.
 
 
 Experience in ETL/ELT, data pipelines, and data integration.
 
 
 Knowledge of CRM/Dataverse or similar enterprise application data models.
 
 
 Experience with Power BI datasets, reporting databases, or analytics platforms.
 
 
 Understanding of APIs, data exchange, and system integration.
 
 
 Good knowledge of data validation, data reconciliation, and data troubleshooting.
 
 
 Strong analytical, problem-solving, and communication skills.
 
</div>

Data Engineer – SQL, Power BI & Dataverse

Systematic

Data and Solutions Engineer - Defence
 Abu Dhabi, UAE
 
About the Role
 Join our UAE Defence Services team and help transform complex military data into actionable insights that support mission-critical decision-making. You will work at the intersection of data engineering, Artificial Intelligence (AI) including agentic, and system integration to deliver operational capabilities across land, maritime, and joint environments.
 
Working closely with Defence customers, operators, and internal teams, you will design, implement, and support datadriven solutions within Systematic’s SitaWare ecosystem, contributing directly to real-world operational effectiveness.
 
Responsibilities
 
Data Integration & Engineering: Ingest, process, and integrate data from multiple sources into unified workflows
 Data Transformation & Pipelines: Design and manage pipelines using low/no-code tools, and business logic
 AI & Agentic Capabilities: Integrate AI services, including agentic workflows, to automate data processing
 System Integration: Configure and integrate systems to enable data exchange across complex architectures
 Visualisation & Reporting: Deliver dashboards, reports, and searchable datasets for operational use
 Solution Delivery: Support end-to-end delivery of mission-critical C4I solutions within scope, time, and quality
 Deployment & Support: Configure, deploy, and provide lifecycle support for operational systems
 Stakeholder Engagement: Engage users and stakeholders to capture requirements, drive solutions and adoption
 Training & Enablement: Train customers on data and AI tools to ensure effective operational use
 Business Development Support: Support proposals, solution scoping, and capture activities, including technical inputs, estimates, and development of demonstrations and PoCs
 
Required Skills & Experience
 
Technical
 
Experience in data engineering, system integration, or similar roles
 Familiarity with data integration tools (e.g., Node-RED, Apache NiFi)
 Experience with APIs, JSON/XML, and data processing
 Exposure to cloud platforms (AWS/Azure)
 Understanding of AI/ML services, models and agentic AI concepts
 
Professional Experience
 
Customer-facing or consultancy experience working with complex stakeholders
 Experience delivering solutions in Defence, security, or government environments
 Experience working in multi-domain operational contexts (advantage)
 
Soft Skills
 
Strong problem-solving and analytical skills
 Excellent communication and stakeholder engagement capabilities
 Ability to work independently and within multidisciplinary teams
 Professional presence with Defence customers
 
Education
 
Bachelor’s or Master’s degree in Computer Science, Data Science, IT, or related field
 
Additional Requirements
 
Fluent in English; Arabic is a strong advantage
 Eligible for UAE security clearance
 Willingness to travel within the region and to HQ as required
 
Why Join Us?
 
Work on mission-critical Defence systems with real-world impact
 Be part of a high-performing, multidisciplinary team
 Engage directly with end users and decision-makers
 Contribute to cutting-edge capabilities spanning data, AI, and simulation
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Get in touch
 
Greta Renner
 
Talent Acquisition Partner
 
.buttontext707a3bac96aae82e a{ border: 1px solid transparent; } .buttontext707a3bac96aae82e a: focus{ border: 1px dashed #1d1d1c !important; outline: none !important; }
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Location: 
Abu Dhabi, Abu Dhabi, AE
 
#job-location.job-location-inline { display: inline; }
 Business Unit: Defence
 Division: Defence Service Delivery
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Data & Solutions Engineer

Bold Technologies

Candidates with the relevant experience only apply.Job SummaryWe are seeking a skilled and motivated Data Center Engineer to support the operation, maintenance, and optimization of mission-critical data center infrastructure. The successful candidate will be responsible for ensuring high availability, reliability, and security of data center facilities, servers, storage, networking equipment, and power/cooling systems.Key Responsibilities<ul><li>Monitor and maintain data center infrastructure, including servers, storage, network devices, UPS systems, and cooling equipment.</li><li>Perform installation, configuration, troubleshooting, and maintenance of hardware and software.</li><li>Manage rack installations, structured cabling, and equipment deployment.</li><li>Monitor environmental conditions and ensure compliance with operational standards.</li><li>Coordinate preventive and corrective maintenance activities.</li><li>Support disaster recovery and business continuity initiatives.</li><li>Maintain documentation, asset inventory, and change management records.</li><li>Work with vendors and service providers for equipment support and maintenance.</li><li>Ensure compliance with security, safety, and operational procedures.</li><li>Participate in on-call support and incident response activities.</li></ul>Qualifications<ul><li>Bachelor's Degree in Computer Science, Information Technology, Electrical Engineering, or related field.</li><li>3&ndash;7 years of experience in Data Center Operations or Infrastructure Management.</li><li>Strong knowledge of:</li><li>Servers (Dell, HPE, Lenovo)</li><li>Storage Systems (NetApp, EMC, Pure Storage)</li><li>Networking (Cisco, Juniper, Arista)</li><li>Virtualization (VMware, Hyper-V)</li><li>Data Center Power &amp; Cooling Systems</li><li>Experience with monitoring tools and DCIM platforms.</li><li>Familiarity with ITIL processes.</li><li>Relevant certifications preferred:</li><li>Cisco CCNA/CCNP</li><li>VMware VCP</li><li>CompTIA Server+</li><li>CDCP/CDCS (Certified Data Centre Professional/Specialist)</li></ul>Application Question(s):<ul><li>Do you have hands on experience with Datacenter projects?</li><li>Please apply if you are acceptable to 5000-7000 AED salary</li><li>How soon you can join?</li></ul>Work Location: In person

Data Center Engineer

Robusta

<div>About the Role
We are seeking an experienced Senior Databricks Data Quality Engineer to lead the design, implementation, and automation of enterprise-scale data quality frameworks within a Databricks environment. The successful candidate will play a key role in establishing data quality controls, profiling frameworks, remediation processes, and AI-assisted quality monitoring across a large-scale data platform consisting of 170+ datasets and over 1,300 Critical Data Elements (CDEs).
This role requires strong expertise in Databricks, PySpark, Delta Lake, MLflow, and modern data quality management practices.
Key ResponsibilitiesData Platform &amp; Databricks Configuration<ul><li>
Configure and manage Databricks workspaces, compute clusters, PySpark notebooks, Delta Lake architecture, and Unity Catalog integrations.
</li><li>Design scalable data quality processing frameworks across 170+ datasets and 1,346 prioritized Critical Data Elements (CDEs).
</li></ul>Data Profiling &amp; Quality Assessment<ul><li>
Develop AI-assisted profiling notebooks using PySpark to establish baseline data quality scores.
</li><li>Assess data quality across six key dimensions including:
</li><li><ul><li>Completeness
</li><li>Uniqueness
</li><li>Validity
</li><li>Consistency
</li><li>Accuracy
</li><li>Timeliness
</li></ul></li><li>Analyze null rates, duplicate records, invalid values, format violations, outliers, and schema drift.
</li></ul>Data Quality Rule Framework<ul><li>
Design and build a scalable Data Quality Rule Factory using parameterized PySpark functions.
</li><li>Enable automated deployment of over 6,700 data quality rules without manual rule-by-rule development.
</li><li>Create reusable rule templates across datasets and data quality dimensions.
</li></ul>Pipeline Quality Enforcement<ul><li>
Integrate data quality controls within Bronze, Silver, and Gold Delta Lake layers.
</li><li>Implement quality gates that prevent data progression unless predefined thresholds are met.
</li><li>Develop reusable Databricks Jobs for automated validation and monitoring.
</li></ul>Data Cleansing &amp; AI-Driven Remediation<ul><li>
Build automated data cleansing pipelines for:
</li><li><ul><li>Standardization
</li><li>Deduplication
</li><li>Schema harmonization
</li></ul></li><li>Deploy MLflow-managed machine learning models for:
</li><li><ul><li>Anomaly detection
</li><li>Fuzzy duplicate detection
</li><li>Exact duplicate identification
</li></ul></li><li>Ensure explainability of model outputs and support human-in-the-loop validation processes.
</li></ul>Exception Management<ul><li>
Design failed-record handling frameworks and quarantine Delta tables.
</li><li>Capture failure reasons, affected CDEs, rule references, and timestamps.
</li><li>Develop automated reprocessing mechanisms for corrected records.
</li></ul>Data Quality Monitoring &amp; Reporting<ul><li>
Build Delta Lake aggregation tables for data quality metrics.
</li><li>Deliver data quality KPIs to Power BI dashboards including:
</li><li><ul><li>Dimension-level scores
</li><li>Rule pass/fail rates
</li><li>SLA adherence metrics
</li></ul></li><li>Configure automated alerting using Databricks SQL Alerts and Azure Monitor.
</li></ul>Predictive Data Quality Analytics<ul><li>
Develop predictive models to identify datasets at risk of quality degradation.
</li><li>Support AI-assisted Root Cause Analysis (RCA) using profiling outputs and machine learning techniques.
</li>Export and prepare remediation datasets for prioritization and governance reporting. 
<li>
</li></ul> 
 
Requirements 
<ul><li>
Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field.
</li><li>5+ years of experience in Data Engineering or Data Quality Engineering.
</li><li>3+ years of hands-on experience with Databricks and PySpark.
</li><li>Strong expertise in Delta Lake architecture and data pipeline development.
</li><li>Experience with Unity Catalog implementation and governance.
</li><li>Hands-on experience with MLflow and machine learning deployment.
</li><li>Strong SQL skills and data modeling expertise.
</li><li>Experience building enterprise-scale data quality frameworks.
</li><li>Experience integrating Databricks with Power BI and Azure services.
</li><li>Strong understanding of data governance, metadata management, and data quality dimensions.
</li></ul>Preferred Qualifications<ul><li>
Microsoft Azure certifications.
</li><li>Databricks Certified Data Engineer Associate or Professional.
</li><li>Experience with enterprise data governance programs.
</li><li>Experience implementing AI-assisted data quality and remediation solutions.
</li><li>Knowledge of Master Data Management (MDM) principles.</li></ul></div>

Senior Data Quality Engineer (4 Months Contract ) Onsite in UAE - Octopus by RTG

Explore 385+ Data engineer in Abu Dhabi this July. Find roles across top companies and apply now to boost your career.