sales engineer

senior data engineer

data analyst

senior software engineer

crm data analyst intern

big data engineer

Global Metrics

<p><b>Vertica Data Engineer </b></p><p><b>Experience :</b> 4+ years (Relevant)<br/><b>Location: </b>Dubai (Onsite)<br/><b>Notice Period : </b>Immediate - 30 days</p><p><b>Job Summary:</b></p><p>As a Vertica Data Engineer, you will be responsible for architecting, developing, and maintaining our Vertica database systems and data pipelines. You will work closely with cross-functional teams, including data scientists, analysts, and developers, to ensure seamless data integration, transformation, and retrieval from Vertica. Your expertise in Vertica's architecture, ETL processes, data modeling, and performance tuning will be crucial in delivering robust and scalable data solutions to support our business objectives. Responsible to migrate data from Oracle, SQL Server to VERTICA Database on timely manner.</p><p><b>1. Roles &amp; Responsibility:</b></p><ul><li>Design and implement efficient data pipelines to extract, transform, and load (ETL) data from various sources into Vertica using Popular ETL Tools like (SAP BODS, INFORMATICA).</li><li>Develop and maintain data models and database structures optimized for high-performance data retrieval and analysis in Vertica.</li><li>Experience in Migrating data from <b>Oracle/SQL Server/SQ Lite</b> to VERTICA Database</li><li>Write Program units (Functions/Procedures) to prepare Data based on the Business requirements.</li><li>Collaborate with data scientists and analysts to understand their data needs and provide scalable solutions to meet analytical requirements.</li><li>Implement data quality checks and data validation processes to ensure the accuracy and integrity of data stored in Vertica.</li><li>Experience in <b>VerticaPy</b> to work with Machine Learning Libraries for Data science use cases</li><li>Work with the DevOps team to ensure smooth deployment, monitoring, and maintenance of Vertica instances.</li><li>Optimize database performance and query execution through indexing, partitioning, and other performance tuning techniques.</li><li>Monitor Vertica database health, troubleshoot performance issues, and proactively address potential bottlenecks.</li><li>Collaborate with data engineers and other stakeholders to define best practices and data governance standards for Vertica usage.</li><li>Stay up-to-date with the latest advancements in Vertica and big data technologies and recommend improvements to existing solutions.</li><li>Document technical specifications, data flows, and architectural designs related to Vertica implementations.</li><li>Provide training and support to end-users to enable them to navigate and interact with Power BI reports effectively</li></ul><p><b>2. Skill Requirements</b>:</p><ul><li>Vertica Certification is a plus.</li><li>Experience with data visualization tools (e.g., Power BI, SAP BI, SAS, Tableau) for data reporting and dashboard creation is beneficial.</li></ul><p><b>4. Qualifications</b></p><ul><li>Bachelor's degree in Computer Science, Information Technology, or a related field</li></ul><p><b>5. Preferred Experience</b></p><p>1. Proven experience as a Data Engineer or similar role with hands-on expertise in designing and managing data solutions in Vertica.</p><p>2. Strong proficiency in SQL and experience with data modeling and schema design in Vertica.</p><p>3. In-depth knowledge of ETL processes and tools, particularly for data integration into Vertica.</p><p>4. Familiarity with other big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure) is advantageous.</p><p>5. Understanding of data warehousing concepts and best practices.</p><p>6. Experience in performance tuning and optimization of Vertica databases.</p><p>7. Familiarity with Linux environments and shell scripting for data-related automation tasks is a plus.</p><p>8. Excellent problem-solving skills and the ability to handle large datasets effectively.</p><p>9. Strong communication and collaboration skills to work effectively within a team-oriented environment.</p><p>10. Self-motivated, with the ability to work independently and manage multiple tasks and projects simultaneously.</p><p>Job Type: Full-time</p><p>Pay: AED12,000.00 - AED17,000.00 per month</p><p>Application Question(s):</p><ul><li>Do you have hands-on expertise in designing and managing data solutions in Vertica?</li></ul><p>Experience:</p><ul><li>Relevant: 4 years (Preferred)</li></ul>

Vertica Data Engineer

<div><div><b><i>About Emirates Global Aluminium</i></b><i>
</i></div><div>Emirates Global Aluminium is the world&rsquo;s biggest &lsquo;premium aluminium&rsquo; producer and the largest industrial company in the United Arab Emirates outside the oil and gas industry. EGA is an integrated aluminium producer, with operations on four continents from bauxite mining to the production of cast primary aluminium and recycling. EGA employs over 7,000 of these people including more than 1,200 UAE Nationals. EGA operates aluminium smelters in Jebel Ali and Al Taweelah in the United Arab Emirates, an alumina refinery in Al Taweelah, a bauxite mine and associated export facilities in the Republic of Guinea, a speciality foundry in high strength recycled aluminium in Germany, and a recycling plant in the United States.</div>
<div><b>
JOB PURPOSE:</b><br>
The Lead Data Ops Engineer will play a critical role in building, scaling, automating, and maintaining the company's Big Data infrastructure and Machine Learning operations (MLOps). This individual will work in close collaboration with our Data Architect, Data Science, Data Engineering, and IT teams to ensure the development, deployment and scale of robust, high-performance data processing systems and ML models.</div><br>
<div></div>
<div><b>KEY ACCOUNTABILITIES:</b></div>
<ul><li><div><b>Big Data Infrastructure:</b> Design, build, and maintain high-performance, cloud-based, fault-tolerant, scalable distributed Data infrastructure that supports the company&rsquo;s data-intensive applications. (Real time/Batch/LLM&rsquo;s). This includes developing strategies for data storage (TB&rsquo;s), processing, and analysis, and implementing high-performance, scalable data pipelines for ML models and data products, supporting up to 50-60 use cases a year and thousands of IoT devices.</div>
</li><li><div>Create infrastructure as Code, perform configuration and set up managed data services. Build and deploy a data science playground for research and prototyping for the professional and citizen data science program being rolled out and supporting 15-20 citizen data scientists/ambassadors.</div>
</li><li><div><b>Machine Learning Operations (MLOps):</b> Develop and manage the ML operational process, working closely with the data science team to implement ML models into production, including edge. This includes streamlining the ML lifecycle, from model development and testing to deployment and implementing the monitoring and alerting strategy.</div>
</li><li><div><b>Automation and Scalability:</b> Implement automation tools and frameworks to manage system updates/changes. Ensure that all systems and infrastructures can scale effectively with the increase in IoT sensors and devices.</div>
</li><li><div><b>Continuous Integration and Deployment (CI/CD):</b> Oversee continuous integration and continuous deployment practices for the data and ML pipeline, ensuring that software can be reliably released at any time.</div>
</li><li><div><b>System Monitoring and Reliability:</b> Monitor system performance and reliability to ensure high levels of performance, availability, and security. This includes identifying and fixing potential and existing system issues. Collaboration and Communication: Strong collaboration with Data Architect/Engineer, data scientists for the implementation and testing of new data services to provide an elastic data infrastructure.</div>
</li><li><div><b>Security:</b> Oversee and ensure that all Big Data and ML Ops platforms comply with the company's security standards and policies.</div>
</li><li><div><b>Mentorship and Leadership:</b> Act as a mentor to junior data members, providing guidance and support in their professional development. Promote a culture of performance, collaboration, and continuous learning within the data team.</div>
</li><li><div><b>Innovation and Continuous Improvement:</b> Stay up-to-date with industry trends and new technologies. Continuously explore innovative solutions and enhancements to the existing data architecture to improve its scalability, reliability, and efficiency.</div>
</li><li><div><b>Problem Solving:</b> Anticipate and resolve technical issues before they become roadblocks, maintaining the continuity of data flow and ensuring the highest levels of data quality and integrity.</div><br>
</li></ul><div></div><div><b>AUTHORITY/DECISION MAKING:</b></div>
<ul><li><div><b>Infrastructure Design:</b> Decide on the most effective design and implementation of the company's Big Data infrastructure.</div>
</li><li><div><b>ML Ops Process:</b> Make key decisions on the ML operational process, ensuring that ML models can be effectively integrated into production.</div>
</li><li><div><b>Automation Tools:</b> Choose the most appropriate automation tools and frameworks for the company's needs.</div>
</li><li><div><b>CI/CD Practices:</b> Determine the best practices for continuous integration and deployment in the context of the company's operations.</div>
</li><li><div><b>System Monitoring:</b> Make decisions on system monitoring strategies, including the selection of tools and responses to system performance metrics.</div>
</li><li><div><b>Security Policies:</b> Have a say in the implementation of security policies as they pertain to the Big Data and ML Ops platforms.</div>
</li><li><div><b>Budget and Costing:</b> Taking ownership of managing data platform costs and relevant data services.</div><br>
</li></ul><div></div><div><b>QUALIFICATIONS &amp; SKILLS:</b></div>
<div><b>Domain Expertise:</b></div>
<ul><li><div>Bachelor&rsquo;s degree required, MS or PhD preferred.</div>
</li><li><div>Bachelor&rsquo;s in Data Science, Computer Science, Engineering, Statistics and 10+ years of relevant experience.</div>
</li><li><div>Experience: A minimum of 5-7 years of experience in a DevOps role, with a focus on managing Big Data infrastructures and MLOps.</div>
</li></ul><div><b>Technical Skills:</b></div>
<ul><li><div>Strong experience with Big Data technologies such as Hadoop, Spark, Kafka, etc.</div>
</li><li><div>Proven expertise in managing and deploying ML models into production.</div>
</li><li><div>Proficient in using CI/CD tools like Jenkins, Travis CI, CircleCI, etc.</div>
</li><li><div>Proficient in using infrastructure automation tools like Terraform, Chef, Puppet, Ansible, etc.</div>
</li><li><div>Strong knowledge of cloud platforms such as Azure (AWS, GCP).</div>
</li><li><div>Experience with containerization technologies like Docker, Kubernetes, etc.</div>
</li><li><div>Familiarity with various database technologies, both SQL and NoSQL.</div>
</li><li><div>Proficiency in programming languages such as Python, Java, or Scala.</div>
</li><li><div>Experience of leveraging MS/Azure ecosystem to manage the development and maintenance of cloud platform operations.</div>
</li><li><div>A broad set of technical skills and knowledge across hardware, software, systems and solutions development.</div>
</li><li><div>A proven track record of using quantitative analysis to impact key business or product decisions.</div>
</li><li><div>Solid grasp of and experience with implementing and operating software development methodologies.</div>
</li><li><div>A solid grasp of common statistical applications and methods (A/B tests and multivariate experiments, probabilities, regression).</div>
</li><li><div>Understanding of Agile Software Development Lifecycle and project planning/execution skills.</div>
</li><li><div>Outstanding communication skills with stakeholders at all levels, managing stakeholders&rsquo; expectations and facilitating discussions across high-risk or complexity under constrained timescales.</div>
</li><li><div>Outstanding capability to establish enterprise-scale data integration procedures across the data development life cycle and ensure that teams adhere to these. Able to manage resources to ensure that data services work effectively at an enterprise level.</div>
</li><li><div>Up to date with data innovation and expert in investigating emerging trends in data-related approaches, performing horizon-scanning for the organization and introducing innovative ways of working.</div>
</li><li><div>Expert in Data integration design and can establish standards and well informed on best practices across different industries. The candidate can distinguish how to keep those standards up to date and ensures adherence to them.</div>
</li><li><div>Good understanding of concepts and principles of data modeling and can produce, maintain and update relevant data models for specific business needs. Also, shows good knowledge on how to reverse-engineer data models from a live system.</div>
</li><li><div>Expert in Metadata management and understands how metadata repositories can support different areas of the business. Capable of promoting and communicating the value of metadata repositories and knows how to set up robust governance processes to keep repositories up to date.</div>
</li><li><div>Expert in identifying and anticipating problems and knowing how to prevent them by linking how problems fit into the larger picture. Has the ability to identify and describe problems, help others to describe them, and build problem-solving capabilities in others.</div>
</li><li><div>Expert in setting up team-based data engineering standards for programming tools and techniques and can select appropriate development methods. Acts as an advisor on the application of standards and methods and ensures compliance while taking technical responsibility for all stages and/or iterations in a software development project, providing method-specific technical advice and guidance to project stakeholders.</div>
</li><li><div>Technical Expert in predicting and advising on data engineering future technology changes that present opportunities for a product or program.</div>
</li><li><div>Experienced with reviewing requirements, specifications and defining test conditions with good understanding on how to identify issues and risks associated with work while being able to analyze and report test activities and results.</div>
</li></ul><div><b>Agile/Digital Experience:</b></div>
<ul><li><div>Experience in Agile Development, with specific Data Engineer/Data Architect (or similar) experience preferred.</div>
</li><li><div>Understands relationships with Product Owner, Agile Coach, Data Scientist, Designer, and the rest of the technical team.</div>
</li></ul><div><b>Individual Skills:</b></div>
<ul><li><div>Exceptional problem-solving skills: demonstrated ability to understand business challenges, structure complex problems, develop solutions.</div>
</li><li><div>Ability to partner and influence key business stakeholders at all levels of the organization.</div>
</li><li><div>Strong skills in team leadership and networking, ability to work across multiple organizations to accomplish diverse goals.</div>
</li><li><div>Exceptional presentation, written, and verbal communication skills.</div>
</li><li><div>Strong communication skills with the ability to align the organization on complex technical decisions.</div>
</li><li><div>Active coach and mentor whose goal is to grow and maximize the team&rsquo;s potential.</div>
</li><li><div>Strong ability and enthusiasm around data strategy and ability to inspire team and organization around the usage of data.</div>
</li></ul><div><b>Mindset &amp; Behaviors:</b></div>
<ul><li><div>High energy and passionate individual who inspires teammates to reach their maximum potential.</div>
</li><li><div>Empathetic coach who can help develop a new group of highly motivated data engineers.</div>
</li><li><div>Excited about trying new solutions outside standard approval.</div>
</li><li><div>Invested in developing a culture of trust, free thought, and complete transparency.</div></li></ul></div>

Lead Data Ops Engineer

VDD AI

<p>We are in search of a talented professional to join our team as a Data Science and Machine Learning Engineer. In this capacity, you'll play a pivotal role in designing, developing, and maintaining advanced data processing and machine learning systems. This is full-time employment.</p><p>www.vdd.ai</p><p><b>Key Responsibilities:</b></p><p>. Design, implement, and validate machine learning models for prediction, classification, recommendation, etc.</p><p>. Select appropriate algorithms and tune hyperparameters to optimize performance.</p><p>. Package models into production-ready systems (e.g., via APIs or cloud services).</p><p>. Handle model drift, data quality issues, and scalability challenges.</p><p>&middot; Build data integration, transformation, and aggregation scripts</p><p>&middot; Develop and implement automation scripts.</p><p>&middot; Monitor and improve the efficiency of scripts&rsquo; runs</p><p>&middot; Create data fetching and application models and controller scripts (MVC applications)</p><p>&middot; Accompany, facilitate, and support data visualisations and insights extractions in applications and BI/Reporting tools.</p><p><b>Requirements:</b></p><p>&middot; Degree in Computer Science, Data Science, Applied Mathematics, or related fields.</p><p>&middot; Record of delivering analytical solutions with business impact</p><p>&middot; Expertise in SQL/Python is mandatory</p><p>&middot; Excellent Microsoft Office skills</p><p>&middot; Understanding of data structures, data modeling, and software architecture.</p><p>&middot; Ability to communicate complex data concepts in a clear and effective manner.</p><p>&middot; A strong knack for problem-solving and a keen eye for detail.</p><p>&middot; Good experience with main clouds (AWS, GCP, Azure) and managed services (Snowflake, Databricks) or similar technologies is highly appreciated.</p><p>Joining our team, you'll have the chance to utilize cutting-edge technologies, collaborate with top-tier professionals, and contribute significantly to our data-driven decision-making processes. If you're passionate about machine learning and data, we'd love to hear from you.</p><p><b>Full Visa Sponsorhip and healthcare. Competitive package!</b></p><p>Job Type: Full-time</p><p>Pay: AED8,000.00 - AED12,000.00 per month</p><p>Ability to commute/relocate:</p><ul><li>Dubai: Reliably commute or planning to relocate before starting work (Required)</li></ul><p>Experience:</p><ul><li>Python: 3 years (Preferred)</li><li>SQL: 3 years (Preferred)</li></ul>

Data Scientist Machine Learner

Washmen

<div><div><b>Position Overview</b></div><div>
We're seeking a self-sufficient Senior Data Engineer to build and scale our data infrastructure supporting product, engineering and analytics team. You'll architect data pipelines, optimize our data platform, and ensure the teams have reliable, high-quality data to drive business decisions.</div><div>
This is a hands-on role for someone who can own the entire data engineering stack - from ingestion to transformation to orchestration. You'll work independently to solve complex data challenges and build scalable solutions.</div><div></div><div><b><br>
Core Responsibilities</b></div><div></div><div><b><br>
Data Pipeline Development &amp; Optimization</b></div><div>
Design, build, and maintain scalable data pipelines using Spark and Databricks</div><div>
Develop ETL/ELT workflows to process large volumes of customer behavior data</div><div>
Optimize Spark jobs for performance, cost efficiency, and reliability</div><div>
Build real-time and batch data processing solutions</div><div>
Implement data quality checks and monitoring throughout pipelines</div><div>
Ensure data freshness and SLA compliance for analytics workloads</div><div></div><div><b><br>
AWS Data Infrastructure</b></div><div>
Architect and manage data infrastructure on AWS (S3, Glue, EMR, Redshift)</div><div>
Design and implement data lake architecture with proper partitioning and optimization</div><div>
Configure and optimize AWS Glue for ETL jobs and data cataloging</div><div>
Shifting Glue jobs to Zero ETL</div><div>
Implement security best practices for data access and governance</div><div>
Monitor and optimize cloud costs related to data infrastructure</div><div></div><div><b><br>
Data Modeling &amp; Architecture</b></div><div>
Design and implement dimensional data models for analytics</div><div>
Build star/snowflake schemas optimized for analytical queries</div><div>
Create data marts for specific business domains (retention, campaigns, product)</div><div>
Ensure data model scalability and maintainability</div><div>
Document data lineage, dependencies, and business logic</div><div>
Implement slowly changing dimensions and historical tracking</div><div></div><div><b><br>
Orchestration &amp; Automation</b></div><div>
Build and maintain workflow orchestration using Airflow or similar tools</div><div>
Implement scheduling, monitoring, and alerting for data pipelines</div><div>
Create automated data quality validation frameworks</div><div>
Design retry logic and error handling for production pipelines</div><div>
Build CI/CD pipelines for data workflows</div><div>
Automate infrastructure provisioning using Infrastructure as Code</div><div></div><div><b><br>
Cross-Functional Collaboration</b></div><div>
Partner with Senior Data Analyst to understand analytics requirements</div><div>
Work with Growth Director and team to enable data-driven decision making</div><div>
Support CRM Lead with data needs for campaign execution</div><div>
Collaborate with Product and Engineering on event tracking and instrumentation</div><div>
Document technical specifications and best practices for the team</div><div>
Work closely with all squads , establish data contracts with engineers to land data in a most optimal way.</div><div></div><div><b><br>
Required Qualifications</b></div><div></div><div><b><br>
Must-Have Technical Skills</b></div><div><b>
Apache Spark</b>: Expert-level proficiency in PySpark/Spark SQL for large-scale data processing - this is non-negotiable</div><div><b>
Databricks</b>: Strong hands-on experience building and optimizing pipelines on Databricks platform - this is non-negotiable</div><div><b>
AWS</b>: Deep knowledge of AWS data services (S3, Glue, EMR, Redshift, Athena) - this is non-negotiable</div><div><b>
Data Modeling</b>: Proven experience designing dimensional models and data warehouses - this is non-negotiable</div><div><b>
Orchestration</b>: Strong experience with workflow orchestration tools (Airflow, Prefect, or similar) - this is non-negotiable</div><div><b>
SQL</b>: Advanced SQL skills for complex queries and optimization</div><div><b>
Python</b>: Strong programming skills for data engineering tasks</div><div></div><div><b><br>
Experience</b></div><div>
6-10 years in data engineering with focus on building scalable data platforms</div><div>
Proven track record architecting and implementing data infrastructure from scratch</div><div>
Experience processing large volumes of event data (billions of records)</div><div>
Background in high-growth tech companies or consumer-facing products</div><div>
Experience with mobile/web analytics data preferred</div><div></div><div><b><br>
Technical Requirements</b></div><div>
Expert in Apache Spark (PySpark and Spark SQL) with performance tuning experience</div><div>
Deep hands-on experience with Databricks (clusters, jobs, notebooks, Delta Lake)</div><div>
Strong AWS expertise: S3, Glue, EMR, Redshift, Athena, Lambda, CloudWatch</div><div>
Proficiency with orchestration tools: Airflow, Prefect, Step Functions, or similar</div><div>
Advanced data modeling skills: dimensional modeling, normalization, denormalization</div><div>
Experience with data formats: Parquet, Avro, ORC, Delta Lake</div><div>
Version control with Git and CI/CD practices</div><div>
Infrastructure as Code: Terraform, CloudFormation, or similar</div><div>
Understanding of data streaming technologies (Kafka, Kinesis) is a plus</div><div></div><div><b><br>
Core Competencies</b></div><div><b>
Self-sufficient</b>: You figure things out independently without constant guidance</div><div><b>
Problem solver</b>: You diagnose and fix complex data pipeline issues autonomously</div><div><b>
Performance-focused</b>: You optimize for speed, cost, and reliability</div><div><b>
Quality-driven</b>: You build robust, maintainable, and well-documented solutions</div><div><b>
Ownership mindset</b>: You take end-to-end responsibility for your work</div><div><b>
Collaborative</b>: You work well with analysts and business stakeholders despite being independent</div><div></div><div><b><br>
Nice-to-Have</b></div><div>
Databricks certifications (Data Engineer Associate/Professional)</div><div>
Experience with dbt for data transformation</div><div>
Knowledge of customer data platforms (Segment, mParticle, Rudderstack)</div><div>
Experience with event tracking platforms (Mixpanel, Amplitude)</div><div>
Familiarity with machine learning infrastructure and MLOps</div><div>
Experience in MENA region or emerging markets</div><div>
Background in on-demand services, marketplaces, or subscription businesses</div><div>
Knowledge of real-time streaming architectures</div><div></div><div><b><br>
What We Offer</b></div><div>
Competitive salary based on experience</div><div>
Ownership of critical data infrastructure and architecture decisions</div><div>
Work with modern data stack and cutting-edge AWS technologies</div><div>
Direct impact on business decisions through data platform improvements</div><div>
Comprehensive health benefits</div></div><div></div>

Senior Data Engineer

emaratech

<div><p>About the Role</p><p>
We are seeking a highly skilled and experienced Data Lake Cloud Engineer with a proven track record of designing, implementing, and maintaining large-scale cloud-based data lake platforms. This role requires a professional who can take ownership of our current data lake ecosystem, optimize its performance, and drive future enhancements with minimal oversight. The ideal candidate will have at least 5 years of hands-on experience in building enterprise-grade data lakes, strong cloud architecture expertise, and the ability to work with cutting-edge data ingestion, processing, and analytics tools.</p><p></p><p><br>
Key Responsibilities</p><br>
<p></p><ul>
<li>
Take ownership of the existing enterprise data lake platform, ensuring scalability, reliability, and performance.</li>
<li>Lead the design, architecture, and implementation of cloud-native data lake solutions and integrations.</li>
<li>Manage and optimize data ingestion pipelines on Oracle OCI, using tools such as Apache NiFi, Kafka, Batch Processing of data, Data captures, and or CSV.</li>
<li>Design and implement pipelines for network data ingestion and file formats (e.g., Parquet, Avro, OCR, etc.), ensuring efficient storage, processing, and retrieval.</li>
<li>Build, configure, and tune query engines such as Trino (Presto), Spark, and Hive for efficient analytics and reporting.</li>
<li>Implement and maintain metadata management, data governance, and security frameworks.</li>
<li>Monitor and troubleshoot system performance, ensuring SLAs are met for ingestion, processing, and query workloads.</li>
<li>Automate platform deployment, monitoring, and maintenance with Infrastructure-as-Code (Terraform, CloudFormation, etc.).</li>
<li>Collaborate with data engineers, analysts, and business teams to understand data requirements and deliver solutions that maximize data accessibility and usability.</li>
<li>Keep the data platform up to date with the latest open-source and cloud-agnostic technologies, implementing upgrades and enhancements where needed.</li></ul><p></p><p><b><br>
Requirements</b></p><p>
5+ years of proven, hands-on experience implementing and managing large-scale data lakes in the cloud (OCI). Strong expertise in:</p><br>
<p></p><ul>
<li>
Data ingestion &amp; orchestration: Apache NiFi, Apache Kafka, CSV, and others</li>
<li>Data processing frameworks: Apache Spark, PySpark, Trino (Presto), Hive, Flink.</li>
<li>Storage &amp; lakehouse architectures: Delta Lake, Apache Hudi, Iceberg, and cloud-native object storage (S3).</li>
<li>Query &amp; analytics tools: Trino/Presto, SparkSQL, Metabase, or Apache Superset.</li>
<li>Experience with data lake file formats such as Apache Parquet, Avro, ORC, CSV, etc. including ingestion, parsing, and analytics within a data lake.</li>
<li>Solid understanding of data governance, lineage, cataloging, and security frameworks (Apache Atlas).</li>
<li>Experience with CI/CD and IaC (ArgoCD, Terraform, Ansible) for automated deployments.</li>
<li>Hands-on experience with cloud security best practices, including IAM, encryption, and network security.</li>
<li>Strong proficiency in Python or Java for data engineering and automation tasks.</li>
<li>Proven ability to work independently, quickly understand existing environments, and deliver results without extensive training.</li></ul><p></p><p><br>
Preferred Skills</p><br>
<p></p><ul>
<li>
Exposure to machine learning workflows integrated with data lakes.</li>
<li>Experience with real-time streaming data pipelines.</li>
<li>Familiarity with containerization and orchestration (Docker, Kubernetes).</li>
<li>Knowledge of cost optimization strategies in cloud-based data platforms.</li></ul></div>

Discovered MENA

<div>
 <p>
  <strong>
   Location
  </strong>
  : Dubai (DIFC) &ndash; Hybrid (2 days remote)
 </p>
 <p>
  <strong>
   This role is Sunday - Thursday
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Why This Role?
  </strong>
 </p>
 <p>
  This is your opportunity to join a
  <strong>
   fast-growing fintech startup
  </strong>
  that&rsquo;s transforming how businesses manage their spending. If you're passionate about building scalable data systems and enabling smarter decisions through clean, actionable data - read on.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What You&rsquo;ll Get to Do
  </strong>
 </p>
 <ul>
  <li>
   Build the next generation of data infrastructure that powers smarter corporate expense management
  </li>
  <li>
   Enable sales and marketing through automation and real-time, data-driven insights
  </li>
  <li>
   Optimize and scale reliable, high-performance databases and analytics pipelines
  </li>
  <li>
   Tackle complex challenges related to data scalability, performance, and compliance
  </li>
  <li>
   Lead data governance initiatives and help shape the company&rsquo;s data strategy
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What You Bring
  </strong>
 </p>
 <ul>
  <li>
   5+ years of experience working with large, complex datasets
  </li>
  <li>
   Expertise in designing and optimizing databases, especially
   <strong>
    PostgreSQL
   </strong>
  </li>
  <li>
   Strong in
   <strong>
    advanced SQL
   </strong>
   , capable of querying and transforming massive data sets
  </li>
  <li>
   Experience with
   <strong>
    dimensional data modeling
   </strong>
   and
   <strong>
    data warehouse schema design
   </strong>
  </li>
  <li>
   Hands-on knowledge of tools like
   <strong>
    Kafka
   </strong>
   ,
   <strong>
    ElasticSearch
   </strong>
   , and
   <strong>
    BigQuery
   </strong>
  </li>
  <li>
   Proficient in
   <strong>
    data streaming platforms
   </strong>
   such as
   <strong>
    mParticle
   </strong>
   ,
   <strong>
    RudderStack
   </strong>
   , or
   <strong>
    Segment
   </strong>
  </li>
  <li>
   Skilled in
   <strong>
    BI and visualization tools
   </strong>
   like
   <strong>
    Looker
   </strong>
   ,
   <strong>
    Tableau
   </strong>
   , or similar
  </li>
  <li>
   Experience deploying infrastructure with
   <strong>
    Terraform
   </strong>
   (Infrastructure-as-Code)
  </li>
  <li>
   Comfortable working within the
   <strong>
    Google Cloud Platform (GCP)
   </strong>
   ecosystem
  </li>
  <li>
   Strong communicator, able to collaborate with both technical and non-technical stakeholders
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Key Responsibilities
  </strong>
 </p>
 <ul>
  <li>
   Design and implement scalable, high-performance data infrastructure
  </li>
  <li>
   Partner with engineering teams to create or improve complex data models
  </li>
  <li>
   Collaborate with business stakeholders to define data requirements and drive decision-making
  </li>
  <li>
   Optimize database performance through schema design, indexing, and sharding
  </li>
  <li>
   Build and maintain both
   <strong>
    batch and streaming
   </strong>
   pipelines for core business functions
  </li>
  <li>
   Support deployments, data migrations, and system upgrades
  </li>
  <li>
   Develop ETL workflows, dashboards, and reports for business visibility
  </li>
  <li>
   Ensure
   <strong>
    data governance
   </strong>
   , including data quality, lineage, and security
  </li>
  <li>
   Ensure
   <strong>
    compliance
   </strong>
   with data regulations in UAE and KSA
  </li>
  <li>
   Contribute to documentation, testing, and continuous improvement of data systems
  </li>
  <li>
   Be available for
   <strong>
    on-call support
   </strong>
   , when required
  </li>
 </ul>
 <p>
 </p>
</div>


Big Fish Recruitment

The Role
<br>Our client is a Dubai-based contracting company under a leading master developer in the country. They are currently seeking for a detail-oriented and experienced Authorities Engineer to manage all authority-related submissions and approvals for their ongoing and upcoming projects. Key Responsibilities: - Act as the primary liaison between the company and local authorities such as Dubai Municipality (DM), RTA, DEWA, DDA, and other relevant entities - Ensure compliance with local codes, regulations, and standards. - Coordinate with consultants, design teams, and project managers to ensure documents meet authority requirements. - Stay updated on changes in regulations and advise project teams accordingly. - Assist in arranging and attending authority inspections when required.
<br><br>
Requirements
<br><ul>
<li>Bachelor’s degree in Civil, Mechanical, or Electrical Engineering or a related field. - Prior experience as an Authorities Engineer within the UAE construction industry IS A MUST. - Strong knowledge of UAE authority procedures and building regulations is mandatory. - Proven track record of successful submissions and approvals with DM, DEWA, RTA, and other UAE regulatory bodies. - Excellent coordination, communication, and follow-up skills.</li>
</ul>
About the company
<br>Service Our aim is to provide our clients and candidates with a consistent, quality service that goes beyond the norm, giving them peace of mind and complete trust in our ability to meet their needs. Knowledge Big Fish consultants specialise in their fields and have extensive experience in the region and beyond. We take pride in our knowledge and network and believe that our relationships are built on trust and integrity and are made for the long term. Care At Big Fish, as well as caring for the people we work with, we also care about the world and environment we live in, that's why Big Fish support initiatives that promote human welfare, environmental protection and sustainability.

Authorities Engineer

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