Senior Data Engineer

NorthBay Solutions

Abu Dhabi

On-site

AED 334,800 - 502,200

Full time

14 days+

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Benefits offered by this job

High-impact projects
Collaborative work environment
Cutting-edge technologies

Job summary

A leading data engineering firm in Abu Dhabi seeks a Senior Data Engineer with 7-10 years of experience. The role involves designing and maintaining scalable data pipelines and optimizing ETL/ELT processes using technologies like Snowflake and Python. Candidates should have strong SQL skills and experience handling large datasets. This onsite position offers the opportunity to work on high-impact projects in a collaborative environment focused on modernizing enterprise data platforms.

Qualifications

  • 7-10 years of professional experience in data engineering.
  • Proficiency in Python is mandatory.
  • Strong SQL expertise and experience with NoSQL databases.
  • Hands-on experience with cloud data warehousing and data lakes.
  • Proven experience designing and managing data pipelines in Snowflake.
  • Experience with large volumes of structured and unstructured data.
  • Exposure to preparing data for ML/GenAI workloads is desirable.

Responsibilities

  • Design, build, and maintain scalable, reliable data pipelines.
  • Develop and optimize ETL/ELT processes for large-scale data.
  • Implement data models and warehouse solutions with Snowflake.
  • Collaborate with data scientists and ML engineers for analytics preparation.
  • Monitor and optimize data workflows for performance.

Skills

Python
SQL
ETL/ELT processes
Data modeling
NoSQL databases
Data governance

Tools

Snowflake
Airflow

Job description

Job Title: Senior Data Engineer
Location: Abu Dhabi UAE (Onsite)
Employment Type: Full-Time Permanent

About the Role

We are seeking a highly skilled Senior Data Engineer with 710 years of experience to join our team in Abu Dhabi. The ideal candidate will have deep expertise in building and optimizing scalable data pipelines working with large datasets and leveraging modern cloud-based technologies. This is an onsite role offering the opportunity to work on cutting-edge data engineering initiatives including data preparation for advanced analytics ML and GenAI use cases.

Key Responsibilities
  • Design build and maintain scalable reliable and high-performance data pipelines.
  • Develop and optimize ETL/ELT processes to handle large-scale structured and unstructured data.
  • Implement data models and warehouse solutions with a focus on Snowflake.
  • Integrate and process data from diverse sources including SQL and NoSQL databases.
  • Ensure data quality governance and security standards are maintained across all systems.
  • Collaborate with data scientists and ML engineers to prepare data for advanced analytics and GenAI models.
  • Work closely with business stakeholders to translate requirements into data engineering solutions.
  • Monitor troubleshoot and optimize data workflows for performance and cost efficiency.
Required Skills & Qualifications
  • Experience: 710 years of professional experience in data engineering.
  • Programming: Proficiency in Python (mandatory).
  • Data Engineering: Strong SQL expertise; experience with NoSQL databases; advanced skills in data modeling ETL/ELT processes and orchestration tools (e.g. Airflow cloud-native services).
  • Cloud: Hands-on experience with cloud data warehousing data lakes and related services (mandatory).
  • Snowflake: Proven experience designing and managing data pipelines/warehousing in Snowflake.
  • Big Data: Experience handling large volumes of structured and unstructured data.
  • Desired Skills: Exposure to preparing data for ML/GenAI workloads; familiarity with data governance and data quality frameworks.
Why Join Us
  • Opportunity to work onsite in Abu Dhabi on high-impact data engineering projects.
  • Collaborative work environment with cross-functional teams in cloud data and ML domains.
  • Chance to contribute to the modernization of enterprise data platforms with cutting-edge technologies.

Required Experience:

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