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.

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