Sr. Expert, Data Architecture

• Design and deliver data products and models that meet business requirements.

• Oversee data quality checks and validation within data engineering processes.

• Ensure data security and access controls are implemented for data products.

• Manage the lifecycle of data products, from development to retirement.

• Collaborate with Data Architects and Data Engineers to build efficient data solutions. Ensures requirements are met and signs off on the data

• Provide technical guidance and thought leadership to the analytics team.

• Maintain production systems reliability through correct utilization of IT standards and governance processes

• Collaborate with business / functional team, develop detailed plans and accurate estimates for completion of build, system testing and implementation of project

Required  Qualifications and skills :

• Proven 7 to 10 years of experience in data solutions including 3 to 5 years as a Data Delivery, data engineer, or in a similar data-focused role with exposure to Safe Agile environment, preferably within FMCG industries.  

• Strong proficiency in data modeling, database design and ETL processes along with Data orchestration tools. In-depth knowledge and extensive hands-on experience working with Apache Airflow, dbt, Python, and Snowflake. Extensive integration experience with all types of data file formats, specifically modern formats including Apache Iceberg, Parquet, and JSON.  AI, ML & Advanced Artificial Intelligence

• Awareness of modern data stack tools, orchestration workflows, BI/analytics reporting (e.g., Power BI) and basic ML/AI pipelines

• Knowledge of data quality frameworks, anomaly detection, data lineage, and privacy/compliance standards

• Proven experience acting as a CI/CD workflow reviewer and approver, ensuring code quality, security, and smooth deployments. Hands-on experience in AI/ML routine integration and applications is desirable.

• Strong background in executing and managing projects using Agile methodologies, with high proficiency in tools such as Snowflake, DBT, Version Management tools - Github and Jira. Experience working with Visualisation tools (e.g., Sigma, DOMO).

• Translating complex technical requirements for non-technical senior business leaders while aligning engineering teams 

• Driving sprint planning, backlog grooming, continuous improvement, and cross-team alignment.

• Problem-Solving & Risk Mitigation: Deconstructing delivery roadblocks, root-cause analysis, and negotiating trade-offs between scope, timeline,

Preferred Qualifications and skills :

• Master in Computer Science with Specialisation in Data Science is preferable.

• Solid understanding of data governance, data security, Metadata management and data quality best practices.

• Familiarity with supply chain processes, analytics, and key performance indicators (KPIs) is highly desirable.

  • Excellent presentation, problem-solving skills, strong communication and collaboration skills to work effectively with IT and business stakeholders.