Senior Data Engineer

Akkodis; Dubai; On-site; AED 350,000 - 600,000; Full time

Job summary

Akkodis in Dubai seeks an experienced Senior Data Engineer to join a growing data and AI team. You will own the full data lifecycle: ingestion, cleansing, transformation, curation and presentation to support analytics, reporting, ML and AI use cases.

You will build robust ETL/ELT pipelines, web-scraping when needed, optimise workloads, and contribute to cloud data architecture while ensuring data quality and security across IAM, encryption and auditing.

Qualifications

• 5+ years in Data Engineering or similar role.
• Strong Python and SQL skills.
• Experience building ETL/ELT pipelines with dbt, Informatica, Talend, AWS Glue, Python or SQL.
• Experience with Snowflake and/or Databricks.
• Cloud exposure: Azure, AWS and/or GCP.
• Data modelling and warehousing fundamentals.
• Experience supporting data lakes and data marts.
• CI/CD and DevOps in data environments.
• Experience with BI/analytical tools (Power BI, Tableau, Spotfire, MicroStrategy).
• Degree in CS/Stats/Math or related field.

Responsibilities

• Develop, test and maintain robust ETL/ELT pipelines.
• Ingest, cleanse, validate and transform data from multiple sources.
• Build data lakes and data marts for analytics and reporting.
• Support ML/AI data pipelines and feature stores.
• Ensure data quality, governance and security practices.
• Collaborate with product, engineering and business teams.
• Contribute to CI/CD, testing and documentation.

Skills

Python

SQL

ETL/ELT pipelines

Data modelling

Data warehousing

CI/CD

DevOps in data

Analytical thinking

Education

Bachelor’s or Master’s degree in Computer Science / Statistics / Mathematics

Tools

dbt

Informatica

Talend

AWS Glue

Snowflake

Databricks

Azure / AWS / GCP

Power BI

Tableau

SAP Analytics Cloud

Job description

We are looking for an experienced Senior Data Engineer to join a growing data and AI team in Dubai. The role will contribute across the full data development lifecycle, including ingestion, cleansing, validation, transformation, curation and presentation. The successful candidate will work closely with data, engineering, product and business teams to deliver secure, scalable data solutions supporting analytics, reporting, machine learning and AI use cases.

Key Responsibilities

• Develop, test and maintain robust ETL/ELT pipelines to ingest and transform data from multiple sources into data lakes and data marts.
• Build and maintain web scraping solutions where required.
• Optimise data workloads for performance and cost, including partitioning, compression and query tuning.
• Apply data modelling standards including dimensional modelling, star/snowflake schemas and canonical data models.
• Contribute to the evolution of the cloud data architecture.
• Support the productionisation of ML, AI and LLM-based solutions through reliable data pipelines and feature stores.
• Expose curated and well-documented datasets for self-service reporting, dashboards and analytical tools.
• Apply strong data quality, governance, metadata management and security practices.
• Implement appropriate controls around IAM, encryption, row/column-level security, auditing and monitoring.
• Partner with Product, Engineering and business stakeholders to translate data requirements into scalable technical solutions.
• Contribute to code reviews, testing, documentation, CI/CD and DevOps practices.
• Develop reusable, maintainable components using clean coding and version control standards.

Requirements

• Minimum 5 years of experience in Data Engineering or a closely related role.
• Strong hands-on experience with Python and SQL.
• Experience building ETL/ELT pipelines using tools such as dbt, Informatica, Talend, AWS Glue, Python or SQL.
• Experience with modern cloud data platforms such as Snowflake and/or Databricks.
• Experience working in Azure, AWS and/or GCP environments.
• Strong understanding of data modelling and data warehousing concepts.
• Experience supporting data lakes, data marts and analytical platforms.
• Familiarity with CI/CD and DevOps practices in data environments.
• Experience working with analytical or BI tools such as Power BI, Tableau, Spotfire, MicroStrategy or SAP Analytics Cloud.
• Strong analytical, troubleshooting and problem-solving capabilities.
• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics or a related discipline.

Preferred Experience

• Experience with SAP HANA / SAP HANA Cloud, including Calculation Views, XS Engine, SDI or SDA.
• Exposure to Large Language Models, Generative AI and Agentic AI solutions.
• Experience building AI workflows or automations using tools such as LangChain, LangGraph, n8n, CrewAI, Make or similar frameworks.
• Experience with feature stores and ML/AI production pipelines.
• Strong understanding of cloud data security and governance.
• Experience building or maintaining robust web scraping solutions.