Senior Data Engineer - EM

Adidas; Dubai; On-site; AED 120,000 - 200,000; Full time

Job summary

A global sports apparel company in Dubai is seeking a Senior Data Engineer to design and optimize scalable data solutions. You will lead the development of the EM Lakehouse platform, ensuring high-quality data practices. The ideal candidate has extensive experience in data engineering, proficiency in Databricks, and leadership skills. This role offers a dynamic environment with opportunities for mentorship and professional growth.

Qualifications

• 7–10 years of experience in data engineering, with some experience in technical leadership.
• Proven track record in data platform operations and governance.
• Background in consumer goods, retail, or similar data-rich industries preferred.
• Fluent in English; additional languages are a plus.

Responsibilities

• Lead the development and optimization of the EM Lakehouse platform (Databricks).
• Design and implement robust data pipelines for ingestion, transformation, and delivery.
• Ensure platform reliability through proactive monitoring and incident management.
• Act as a technical liaison between engineering and business teams.
• Mentor junior engineers and contribute to their technical development.

Skills

Advanced proficiency in Databricks

Spark

Python

SQL

Cloud-native platforms (Azure, AWS)

ETL / ELT pipelines

Orchestration tools (Airflow, Azure Data Factory)

Infrastructure-as-code (Terraform)

Data governance tools (Unity Catalog)

DevOps practices

Education

Bachelor’s or Master’s degree in Computer Science

Job description

Senior Data Engineer

Purpose & Overall Relevance for the Organization :

As a Senior Data Engineer within the Data & Analytics (DNA) team for Emerging Markets (EM), you will play a pivotal role in designing, building, and optimizing the region’s data infrastructure. You will lead the execution of scalable, high-quality, and compliant data solutions that support reporting, analytics, and data products across the business. This role serves as a technical senior figure and mentor within the engineering team, driving excellence in data engineering practices and contributing to strategic initiatives.

Key Responsibilities :

Data Engineering & Platform Ownership

• Lead the development and optimization of the EM Lakehouse platform (Databricks).
• Design and implement robust data pipelines for ingestion, transformation, and delivery across multiple systems.
• Ensure platform reliability through proactive monitoring and incident management.
• Contribute to sprint planning and oversee execution of engineering tasks.

Data Governance & Quality

Enforce data compliance and access control policies (e.g., Row-Level Security).

Develop and maintain data quality frameworks, including SLA tracking and anomaly detection.

Ensure proper metadata management, lineage tracking, and documentation.

Innovation & Optimization

Drive continuous improvement in engineering processes and delivery cycles.

Evaluate and implement scalable solutions to enhance performance and reduce costs.

Prototype and integrate emerging technologies to improve data infrastructure.

Stakeholder Collaboration

Act as a technical liaison between engineering, BI Analytics, Global Platform teams, and Data Domain owners.

Facilitate alignment on architecture, priorities, and delivery timelines.

Represent the engineering team in cross-functional discussions with Hubs and Clusters.

Leadership & Team Management

Mentor junior engineers and contribute to their technical development.

Support resource planning and task allocation within the engineering team.

Promote a culture of agile delivery, collaboration, and continuous learning.

Training & Coaching

Lead technical workshops and share best practices across the team.

Contribute to internal documentation and training materials.

Others

Special projects : Participate in strategic cross-functional initiatives and innovation programs.

Knowledge , Skills and Abilities :

Technical Expertise

Advanced proficiency in Databricks, Spark, Python, SQL.

Strong understanding of cloud-native platforms (Azure, AWS).

Experience with ETL / ELT pipelines, orchestration tools (Airflow, Azure Data Factory), and CI / CD.

Familiarity with data governance tools (Unity Catalog), observability frameworks (Great Expectations, Monte Carlo).

Exposure to infrastructure-as-code (Terraform) and DevOps practices.

Awareness of cloud cost optimization strategies.

Leadership & Strategy

Ability to lead technical initiatives and mentor team members.

Strong problem-solving and decision-making skills.

Effective communicator with the ability to influence stakeholders.

Requisite Education and Experience / Minimum Qualifications :

7–10 years of experience in data engineering, with some experience in technical leadership.

Proven track record in data platform operations and governance.

Background in consumer goods, retail, or similar data-rich industries preferred.

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.

Fluent in English; additional languages are a plus.