project engineer

planning engineer

estimation engineer

devops engineer

sales engineer

data engineer

Dicetek LLC

<div>
 Role Overview
 <br/>
 <br/>
 We are seeking a highly skilled and motivated Data Engineer with 5&ndash;7 years of experience to design, build, and optimize scalable data pipelines and platforms. The ideal candidate will have strong expertise in SQL, Databricks, Confluent (Kafka), Azure Data Factory (ADF), and Azure Data Lake Storage (ADLS), with a solid understanding of banking domain processes and regulatory considerations. This role involves working closely with cross-functional teams to enable data-driven decision-making across critical banking functions.
 <br/>
 <br/>
 Key Responsibilities
 <br/>
 <br/>
 <ul>
  <li>
   Design, develop, and maintain robust, scalable data pipelines using Azure Data Factory (ADF) and Databricks
  </li>
  <li>
   Implement batch and real-time data ingestion frameworks leveraging Confluent Kafka
  </li>
  <li>
   Build and optimize data models, transformations, and ETL/ELT pipelines using SQL and Spark
  </li>
  <li>
   Develop and manage data storage solutions in Azure Data Lake Storage (ADLS)
  </li>
  <li>
   Ensure high data quality, integrity, and governance standards
  </li>
  <li>
   Support data integration across systems including core banking and CRM
  </li>
  <li>
   Optimize performance of large-scale datasets
  </li>
  <li>
   Collaborate with stakeholders to translate requirements into solutions
  </li>
  <li>
   Ensure compliance with banking regulations and data privacy
  </li>
  <li>
   Troubleshoot production issues
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Required Skills &amp; Experience
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Strong expertise in SQL (complex queries, tuning, modeling)
  </li>
  <li>
   Hands-on experience with Databricks, Spark, PySpark
  </li>
  <li>
   Experience with Confluent Kafka and event-driven architecture
  </li>
  <li>
   Experience with Azure Data Factory (ADF)
  </li>
  <li>
   Experience with Azure Data Lake Storage (ADLS)
  </li>
  <li>
   Understanding of data warehousing concepts
  </li>
  <li>
   Familiarity with CI/CD and DevOps for data platforms
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Domain Knowledge (Preferred)
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience in banking or financial services
  </li>
  <li>
   Understanding of core banking systems
  </li>
  <li>
   Knowledge of payments, lending, wealth management
  </li>
  <li>
   Awareness of regulatory frameworks (KYC, AML)
   <br/>
   <br/>
  </li>
 </ul>
 Soft Skills
 <br/>
 <br/>
 <ul>
  <li>
   Strong analytical and problem-solving skills
  </li>
  <li>
   Excellent communication and stakeholder engagement
  </li>
  <li>
   Ability to work in fast-paced environments
  </li>
  <li>
   Strong ownership and collaboration mindset
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor&rsquo;s or Master&rsquo;s degree in relevant field
  </li>
  <li>
   Azure/Data engineering certifications preferred
   <br/>
   <br/>
  </li>
 </ul>
 Good to Have
 <br/>
 <br/>
 <ul>
  <li>
   Experience with Python or Scala
  </li>
  <li>
   Exposure to data governance tools
  </li>
  <li>
   Knowledge of APIs and microservices
  </li>
  <li>
   Experience with BI tools like Power BI
  </li>
 </ul>
</div>


Data Engineer

Heidelberg Materials Trading

<div>
 <p>
  Heidelberg Materials Trading is the international trading arm of Heidelberg Materials, one of the world&rsquo;s largest building materials companies, handling overseas drybulk product exports and imports across global markets. We are looking for a talented individual to join our IT team in our Dubai Office as:
 </p>
 <p>
 </p>
 <p>
  <strong>
   Data Engineer
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   About the Role:
  </strong>
 </p>
 <p>
  This role sits at the centre of a greenfield transformation initiative, where we are replacing legacy reporting workflows with a modern, Microsoft first cloud data platform. You will work directly with IT and business stakeholders to connect our front office (Salesforce) and back office (JD Edwards ERP) systems into a unified analytics layer powering business critical Power BI dashboards. The role requires a hands on technical developer who builds, and owns data pipelines end-to-end, and can operate pragmatically within a Microsoft Fabric&ndash;oriented environment while proposing justified alternatives when needed.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Key Responsibilities:
  </strong>
 </p>
 <ul>
  <li>
   Lead the migration of reporting from QlikSense to Power BI, ensuring accurate replication of existing logic, KPIs, and reporting workflows.
  </li>
  <li>
   Design, build, and maintain scalable Azure SQL&ndash;based data pipelines to support analytics, reporting, and operational decision making.
  </li>
  <li>
   Build and optimise Power BI data models, reusable datasets, and semantic layers following best practice modelling principles.
  </li>
  <li>
   Integrate data from JD Edwards (ERP), Salesforce (CRM), and other business systems, ensuring accuracy, consistency, and reliability across the reporting lifecycle.
  </li>
  <li>
   Reverse engineer manual Excel-based workflows and translate them into automated SQL or Python based pipelines to improve efficiency and reliability.
  </li>
  <li>
   Implement data validation, quality checks, monitoring, and performance optimisation across the data platform and reporting layers.
  </li>
  <li>
   Deliver Power BI training for business users and create documentation, dashboards, and best practice materials.
  </li>
  <li>
   Work closely with cross-functional teams to understand business requirements and translate them into scalable, maintainable data and reporting solutions.
  </li>
  <li>
   Contribute to data governance, security standards, and consistent documentation practices.
  </li>
  <li>
   Support UAT cycles, phased go lives, and iterative enhancements to reporting processes.
  </li>
 </ul>
 <p>
 </p>
 <p>
  <strong>
   Qualifications:
  </strong>
 </p>
 <ul>
  <li>
   Bachelor&rsquo;s degree in Computer Science, Data Engineering, Information Systems, or a related field.
  </li>
  <li>
   Minimum 3 years of hands‑on experience in data engineering or data platform development. - Minimum 6 years for senior consideration.
  </li>
  <li>
   Strong SQL skills with experience working on relational databases and transformation logic.
  </li>
  <li>
   Hands‑on experience with Power BI (DAX, data modelling, row‑level security, performance optimisation).
  </li>
  <li>
   Experience developing ETL/ELT pipelines using Azure Data Factory, Azure Synapse, or Microsoft Fabric (experience with at least one is required).
  </li>
  <li>
   Experience integrating ERP or CRM systems such as JD Edwards, SAP, or Salesforce, with a strong advantage for candidates familiar with these architectures.
  </li>
  <li>
   Solid understanding of transactional vs analytical modelling and modern data warehousing approaches.
  </li>
  <li>
   Comfortable operating as a hands‑on builder, capable of developing, testing, and shipping data pipelines independently.
  </li>
  <li>
   Strong communication skills with the ability to translate technical detail into clear business language.
  </li>
  <li>
   Able to work within a Microsoft‑first environment while recommending alternative tools when supported by a clear business case.
  </li>
  <li>
   Exposure to Microsoft Power Platform (Power Automate, Power Apps) is an advantage.
  </li>
  <li>
   Experience in trading, logistics, or supply chain environments is beneficial.
  </li>
  <li>
   Familiarity with Azure‑based cloud data architectures is preferred.
  </li>
 </ul>
 <p>
 </p>
 <p>
 </p>
 <p>
  <strong>
   We thank all applicants for their interest, but only shortlisted candidates will be contacted.
  </strong>
 </p>
 <p>
  <strong>
   All applications will be kept strictly confidential.
  </strong>
 </p>
</div>


Maaloomatiia Academy

<div>
 <strong>
  Job Title
  <br/>
  <br/>
 </strong>
 <strong>
  Cloudera Data Engineer
  <br/>
  <br/>
 </strong>
 <strong>
  Job Scope
  <br/>
  <br/>
 </strong>
 We are seeking an experienced
 <strong>
  Cloudera Data Engineer
 </strong>
 with strong hands-on expertise in
 <strong>
  Cloudera CDP, Hadoop, Spark, Hive, and HDFS
 </strong>
 . The ideal candidate will be responsible for building and maintaining big data pipelines, optimizing data workflows, and supporting production environments to ensure reliability and performance.
 <br/>
 <br/>
 <strong>
  Main Duties And Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design, build, and maintain big data pipelines using Cloudera CDP components.
  </li>
  <li>
   Develop and optimize ETL/ELT workflows using Spark, Hive, and Hadoop ecosystems.
  </li>
  <li>
   Manage and maintain HDFS storage, ensuring high availability and performance.
  </li>
  <li>
   Perform production support activities, including issue resolution, monitoring, and performance tuning.
  </li>
  <li>
   Work with data scientists, analysts, and other engineering teams to support data-driven initiatives.
  </li>
  <li>
   Ensure data governance, security, and compliance across big data environments.
  </li>
  <li>
   Troubleshoot cluster-level issues related to resource utilization, scheduling, and configuration.
  </li>
  <li>
   Participate in solution design, architecture discussions, and technical documentation.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Position Requirements
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Strong hands-on experience with Cloudera CDP.
  </li>
  <li>
   Proficiency in Hadoop ecosystem: HDFS, YARN, MapReduce, Hive, Impala.
  </li>
  <li>
   Strong experience working with Apache Spark (PySpark or Scala preferred).
  </li>
  <li>
   Solid understanding of distributed systems and big data architecture.
  </li>
  <li>
   Experience with production support and troubleshooting in big data environments.
  </li>
  <li>
   Strong SQL skills and experience optimizing large-scale queries.
  </li>
  <li>
   Familiarity with Linux, shell scripting, and automation tools.
  </li>
  <li>
   Experience with version control (Git) and CI/CD workflows is a plus.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Education
  <br/>
  <br/>
 </strong>
 Bachelor's degree in Computer Science or any other related field
 <br/>
 <br/>
 <strong>
  Experience
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience with cloud platforms (AWS, Azure, GCP) for big data workloads.
  </li>
  <li>
   Exposure to Kafka, NiFi, Oozie, or similar data orchestration tools.
  </li>
  <li>
   Knowledge of Docker, Kubernetes, or containerized environments.
  </li>
  <li>
   Understanding of security, encryption, and data governance concepts.
  </li>
 </ul>
</div>


Cloudera Data Engineer

MultiBank Group

<div>
 <p>
  Welcome to
  <strong>
   MultiBank Group
  </strong>
  , a global financial pioneer established in 2005 in California and now proudly headquartered in Dubai, UAE. We specialize in delivering cutting-edge trading technology, unparalleled liquidity, and exceptional customer service. Our extensive range of financial products includes Forex, Metals, Shares, Indices, Commodities, and Cryptocurrency CFDs.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Join our thriving community of over 2 million clients across 100 countries, contributing to a daily trading volume exceeding US$ 35 billion. As a heavily regulated institution with oversight from 18+ financial regulators across 5 continents, and recipient of over 80 financial awards, MultiBank Group is devoted to innovation, excellence, and empowering our clients to achieve their financial goals.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Role Overview:
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  We are seeking an experienced
  <strong>
   AI Data Engineer
  </strong>
  to design, develop, and deploy innovative data and machine learning solutions that drive customer engagement, retention, and lifetime value (LTV). This role will focus on building scalable data pipelines, predictive models, and GenAI-powered applications that enable more personalised trading experiences and support data-driven decision-making across the business.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Key Responsibilities:
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   Collaborate with the wider marketing department to build meaningful datasets and a centralised data warehouse that will be used for reporting across numerous teams, focused on customer retention and LTV.
  </li>
  <li>
   Develop and own machine learning solutions that specialise in customer personalisation to increase engagement and coordinate with marketing teams towards their strategy and execution across multiple channels, especially around predictive modelling, churn prediction and customer segmentation.
  </li>
  <li>
   Explore the capabilities of Gen AI to develop new apps for our traders that make trading easier and more personalised based on their preferences.
  </li>
  <li>
   Maintain a commercial acumen and find opportunities where technology can be used to increase customer engagement or automate internal tasks.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Qualifications &amp; Requirements:
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   Strong expertise in SQL, comfortable with raw data and multiple high-volume datasets such as customer journey, marketing performance or product behaviour.
  </li>
  <li>
   Comfortable creating pipelines and automations with Python to connect multiple endpoints and APIs such as first party databases, marketing platforms or other data collection platforms.
  </li>
  <li>
   Expertise in using Python todeploy machine learning solutions end to end, especially around predictive modelling and customer segmentation.
  </li>
  <li>
   Previous experience in finding customer insights through data analysis, communicating it to different stakeholders and strategizing on how to increase customer engagement and LTV.
  </li>
  <li>
   Capable of creating applications using LLMs that summarise high volumes of data and knowledge of the latest Gen AI use cases.
  </li>
  <li>
   Previous exposure to
   <strong>
    ETL tools
   </strong>
   (e.g., dbt, AWS Glue) and cloud environments (preferably
   <strong>
    AWS, SageMaker
   </strong>
   ).
  </li>
  <li>
   Strong communication skills with the ability to present complex data insights to non-technical stakeholders and support business strategy.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Why Join Us?
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   Work with an industry-leading global financial institution.
  </li>
  <li>
   Competitive salary and comprehensive employee benefits.
  </li>
  <li>
   Opportunities for professional growth and career advancement.
  </li>
  <li>
   Collaborative, inclusive, and dynamic work environment.
  </li>
  <li>
   Commitment to innovation and professional excellence.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <em>
   Become part of our international community at MultiBank Group, dedicated to excellence, innovation, and shaping the future of finance.
  </em>
 </p>
</div>


AI Data Engineer

TALENTMATE

<div>
 <strong>
  Job Description
  <br/>
  <br/>
 </strong>
 <strong>
  Job Description
  <br/>
  <br/>
 </strong>
 <strong>
  Overview
  <br/>
  <br/>
 </strong>
 <strong>
  About Presight
  <br/>
  <br/>
 </strong>
 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.
 <br/>
 <br/>
 <strong>
  The Opportunity
  <br/>
  <br/>
 </strong>
 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.
 <br/>
 <br/>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <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.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Qualifications:
  <br/>
  <br/>
 </strong>
 <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.
   <br/>
   <br/>
  </li>
 </ul>
 Job Details
 <br/>
 <br/>
 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/
 <br/>
 <br/>
 Sector: Other
 <br/>
 <br/>
 What We Offer
 <br/>
 <br/>
 <strong>
  About The Company
  <br/>
  <br/>
 </strong>
 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.
 <br/>
 <br/>
 Report
 <br/>
 <br/>
 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>


Senior Data Engineer

Deriv.com

<div><h3 class="jobSectionHeader"><b>Job Information</b></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>
<br><div><h3 class="jobSectionHeader"><b>Job Description</b></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.<br>
<br>
</div><div></div><br>
<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.<br>
<br>
</div><p></p><br>
<br>
<div><b>Why This Matters</b><br>
<br>
</div><div></div><br>
<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.<br>
<br>
</div><div></div><br>
<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.<br>
<br>
</div><p></p><br>
<br>
<div><b>Why Deriv</b><b><br>
</b><br>
</div><div></div><br>
<div>We&rsquo;re in production, not planning.
<br>
</div><ul><li>Natural language interfaces querying the data warehouse directly&mdash;leaders ask questions in English, answers come back in seconds
<br>
</li><li>Continuous KPI monitoring with anomaly detection surfacing problems before stakeholders notice
<br>
</li><li>Dozens of fraud detection models running against production data, continuously
<br>
</li><li>400+ users on our internal workflow orchestration platform, fed by the data infrastructure you&rsquo;ll help build and scale
<br>
</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.<br>
<br>
</div><p></p><br>
<br>
<div><b>What You&rsquo;ll Do</b><br>
<br>
</div><div></div><br>
<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.<br>
<br>
</div><div></div><br>
<div><b>Build pipelines that are governed by design</b><b>
</b><br>
</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
<br>
</li><li>Bake in observability from the start: freshness checks, completeness monitoring, schema drift detection, lineage tracking, and alerting. Not retrofitted after launch
<br>
</li>Implement automated data quality checks and anomaly detection into every pipeline&mdash;governance built in, not bolted on<br>
<li>
<br>
</li></ul><div></div><br>
<div><b>Own data accuracy before anyone has to ask</b><b>
</b><br>
</div><ul><li>Identify and resolve data issues before they surface to analysts or stakeholders
<br>
</li><li>Define and maintain data contracts: SLAs, SLOs, schema agreements, and producer-consumer alignment
<br>
</li>Handle PII, access control, and auditability correctly in a regulated financial environment<br>
<li>
<br>
</li></ul><div></div><br>
<div><b>Make the platform better than you found it</b><b>
</b><br>
</div><ul><li>Optimise warehouse performance and cost&mdash;query efficiency, partitioning, clustering, orchestration reliability
<br>
</li><li>Build data models designed to scale beyond the immediate use case: dimensional modelling, semantic layers, reusable abstractions
<br>
</li>Spot gaps in the data platform and address them without waiting to be assigned<br>
<li>
<br>
</li></ul><div></div><br>
<div><b>Raise the bar for the team</b><b>
</b><br>
</div><ul><li>Partner with analysts, product, finance, and compliance teams to translate requirements into reliable, governed data products
<br>
</li><li>Peer-review pipeline code and push quality standards higher across the team
<br>
</li>Help onboard new engineers&mdash;share context, catch mistakes early, make others productive faster<br>
<li>
<br>
<br>
</li></ul><p></p><br>
<div><b>Who You Are</b><br>
<br>
</div><div></div><br>
<div><b>You build pipelines, not just queries</b><b>
</b><br>
</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.<br>
<ul><li>
<br>
</li></ul><div></div><br>
<div><b>You know the cloud data stack cold</b><b>
</b><br>
</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.<br>
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<div><b>You think in contracts, not assumptions</b><b>
</b><br>
</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.<br>
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<div><b>You fix root causes, not symptoms</b><b>
</b><br>
</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.<br>
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<div><b>You make the people around you better</b><b>
</b><br>
</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.<br>
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<div><b>You&rsquo;ve seen what regulated data looks like</b><b>
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</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.<br>
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<div><b>Tech Stack</b><b>
</b><br>
</div><ul><li>Cloud &amp; Warehouse: GCP, BigQuery
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</li><li>Orchestration: Airflow
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</li><li>Languages: Python, SQL
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</li><li>Transformation: dbt / Dataform
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</li><li>Streaming: Kafka, Pub/Sub
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</li>Practices: CI/CD, version-controlled pipelines, peer review, AI-assisted development<br>
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</li></ul><p></p><br>
<div><b>The Honest Reality</b><br>
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</div><div></div><br>
<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.<br>
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<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.<br>
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<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><p></p>

GSSTech Group

<div><p>We are seeking an experienced Data Engineer with strong expertise in Python, Microservices Architecture, Data Transformation, and Backend Engineering to join our Data Engineering team. The ideal candidate will be responsible for designing and developing scalable backend services, data processing frameworks, RESTful APIs, and data transformation pipelines that support enterprise data-driven applications.</p><p>
This role requires strong hands-on experience with Python-based web frameworks, database technologies, ETL pipelines, microservices, API security, and modern software engineering practices. Candidates should have experience building production-grade applications with a focus on scalability, reliability, security, and performance.</p><b><br>
Requirements</b><p><br>
Key Responsibilities</p><ul><li>Design, develop, and maintain scalable backend applications and web frameworks using Python.</li><li>Build robust RESTful APIs and microservices to serve enterprise datasets and business applications.</li><li>Develop and optimize data transformation pipelines to process, clean, enrich, and prepare data for analytics and business consumption.</li><li>Design and implement scalable data access layers integrating multiple relational and NoSQL databases.</li><li>Collaborate with frontend developers to integrate user-facing components with backend services.</li><li>Ensure applications are secure, highly available, performant, and maintainable.</li><li>Design and maintain database schemas and data models aligned with business requirements.</li><li>Implement ETL processes for extracting, transforming, and loading large-scale datasets.</li><li>Optimize database performance, query execution, and data retrieval mechanisms.</li><li>Troubleshoot production issues and implement scalable solutions for long-term platform stability.</li><li>Participate in code reviews, testing activities, technical design discussions, and engineering best practices.</li><li>Work closely with business stakeholders, architects, and engineering teams within Agile delivery environments.</li></ul><p>
Required Technical Skills</p><p>
Python Development</p><ul><li>Strong hands-on experience in Core Python development.</li><li>Expertise in building backend services and APIs using Python.</li><li>Strong understanding of object-oriented programming principles and software design patterns.</li><li>Experience writing clean, reusable, maintainable, and production-quality code.</li></ul><p>
Web Frameworks &amp; API Development</p><p>
Strong experience with one or more Python frameworks including:</p><ul><li>FastAPI</li><li>Flask</li><li>Django</li><li>Pyramid</li></ul><p>
Experience with:</p><ul><li>RESTful API design and development</li><li>API versioning and documentation</li><li>Routing and middleware implementation</li><li>Authentication and authorization</li><li>Framework testing and debugging</li></ul><p>
Microservices Architecture</p><ul><li>Strong experience designing and developing microservices-based applications.</li><li>Deep understanding of distributed systems architecture.</li><li>Experience building scalable and resilient service-oriented platforms.</li><li>Knowledge of service communication patterns and API orchestration.</li><li>Experience handling concurrent requests and high-volume transaction processing.</li></ul><p>
Asynchronous Programming</p><ul><li>Strong understanding of asyncio and asynchronous programming concepts.</li><li>Experience handling concurrent connections and non-blocking operations.</li><li>Knowledge of performance optimization for I/O-intensive applications.</li></ul><p>
Security &amp; API Protection</p><ul><li>Strong understanding of API and microservices security best practices.</li><li>Experience implementing:</li></ul><ul><li>
OAuth 2.0</li><li>
JWT Authentication</li><li>
API Gateway integrations</li><li>
Encryption and secure communication protocols<br>
<ul><li>Experience implementing authentication, authorization, and access control mechanisms.</li></ul></li></ul><p>
Database &amp; ORM Expertise</p><ul><li>Strong experience with relational and NoSQL databases.</li><li>Experience designing database schemas and optimizing database performance.</li><li>Strong proficiency with:</li></ul><ul><li>
SQL</li><li>
PostgreSQL</li><li>
MySQL</li><li>
MongoDB</li><li>
Redis</li></ul><p>
Hands-on experience with ORMs including:</p><ul><li>SQLAlchemy</li><li>Django ORM</li></ul><p>
Ability to:</p><ul><li>Define models</li><li>Perform CRUD operations</li><li>Write optimized queries</li><li>Handle transactions</li><li>Manage database migrations</li></ul><p>
Data Engineering &amp; Transformation</p><ul><li>Experience building and maintaining ETL pipelines.</li><li>Strong understanding of data transformation, enrichment, aggregation, and cleansing techniques.</li><li>Experience ensuring data quality, consistency, and integrity.</li><li>Ability to support analytical and data-driven applications through scalable processing frameworks.</li></ul><p>
DevOps &amp; CI/CD</p><ul><li>Experience building and maintaining CI/CD pipelines.</li><li>Experience deploying and supporting production-grade applications.</li><li>Understanding of infrastructure automation and modern software delivery practices.</li><li>Experience with release management and deployment workflows.</li></ul><p>
Big Data &amp; Data Technologies</p><p>
Exposure to technologies such as:</p><ul><li>Hadoop</li><li>Apache Spark</li><li>Apache Kafka</li></ul><p>
Understanding of:</p><ul><li>Data Warehousing concepts</li><li>Distributed data processing</li><li>Enterprise data architectures</li></ul><p>
Version Control &amp; Development Practices</p><ul><li>Strong experience with Git version control.</li><li>Experience with:</li></ul><ul><li>
Branching strategies</li><li>
Code reviews</li><li>
Pull Requests</li><li>
Merge conflict resolution</li><li>
Collaborative development workflows</li></ul><p>
Testing &amp; Debugging</p><ul><li>Experience with:</li></ul><ul><li>
Unit Testing</li><li>
Integration Testing</li><li>
Logging</li><li>
Monitoring</li><li>
Performance Troubleshooting</li><li>
Production Support</li></ul><p>
Nice to Have</p><ul><li>Experience with AWS, Azure, or GCP.</li><li>Experience with Docker and Kubernetes.</li><li>Exposure to cloud-native architectures.</li><li>Knowledge of data governance, compliance, privacy, and security standards.</li><li>Experience supporting large-scale enterprise data platforms.</li></ul><p>
Required Competencies</p><ul><li>Strong analytical and problem-solving skills.</li><li>Excellent communication and stakeholder management capabilities.</li><li>Strong collaboration and teamwork skills.</li><li>Ability to work effectively in Agile/Scrum environments.</li><li>Strong ownership mindset with attention to detail.</li><li>Ability to document solutions and communicate technical concepts clearly.</li></ul><p>
Education</p><p>
Bachelor&rsquo;s Degree in Computer Science, Information Technology, Engineering, Data Engineering, or a related field.</p></div><p></p>

Data Engineer - Python & Microservices

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Data Engineer - Python & Microservices