Background information about the job or company (e.g., role context, company overview)

Every day 8,000 children die and 2 billion people suffer from preventable illnesses because their diets lack basic vitamins and minerals. Sanku has the solution. Our vision: a world where everyone, everywhere, has guaranteed, affordable access to the nutrients they need to survive and thrive. Billions of people rely on small flour mills for their daily fo...

As our Data Engineer, you’ll be a crucial force driving the design, development, and optimization of data infrastructure. This isn’t just a job, it’s an opportunity to shape meaningful change by building reliable data pipelines and systems that enable better decision-making, program monitoring, and impact measurement. You’ll collaborate with a passionate team to deliver solutions that directly improve lives and accelerate our mission.

Responsibilities or duties

• Monitor and maintain robust data pipelines on AWS, using Apache Airflow, SQL and Python to build, optimize, and automate ETL processes.
• Use CloudWatch and other tools to track performance, debug issues, and ensure continuous data flow and system reliability.
• Manage and optimize SQL databases, including writing, testing, and documenting scripts for operational metrics and reporting.
• Validate and clean extracted data using automated processes and custom algorithms to ensure accuracy and consistency.
• Collaborate with Data Scientists and Analysts to support data-driven strategies and resolve technical data pipeline issues.
• Identify and recommend system improvements to meet evolving data needs and support cross-functional teams effectively.
• Administer data governance processes, defining metadata standards and maintaining data clarity across systems.
• Ensure data quality, integrity, privacy, and compliance with applicable data protection regulations.

Qualifications or requirements (e.g., education, skills)

• Bachelor’s Degree in Computer Science, Data Science, Engineering or a related field.
• Demonstrated ability to build scalable data models and data pipelines.
• Familiarity with big data tools and environments, coupled with strong problem-solving skills and analytical thinking.
• Proficiency in the Data stack: AWS Ecosystem (S3, RDS, EC2, VPC etc), SQL, Apache Airflow, CloudWatch, REST APIs, Postman, Python, Git & GitHub, Scripting, etc.

Experience needed

• Minimum of 5 years of progressive experience in data engineering, especially in large scale and complex FMCG data environments.

• Monitor and maintain robust data pipelines on AWS, using Apache Airflow, SQL and Python to build, optimize, and automate ETL processes.
• Use CloudWatch and other tools to track performance, debug issues, and ensure continuous data flow and system reliability.
• Manage and optimize SQL databases, including writing, testing, and documenting scripts for operational metrics and reporting.
• Validate and clean extracted data using automated processes and custom algorithms to ensure accuracy and consistency.
• Collaborate with Data Scientists and Analysts to support data-driven strategies and resolve technical data pipeline issues.
• Identify and recommend system improvements to meet evolving data needs and support cross-functional teams effectively.
• Administer data governance processes, defining metadata standards and maintaining data clarity across systems.
• Ensure data quality, integrity, privacy, and compliance with applicable data protection regulations.

• AWS Ecosystem (S3, RDS, EC2, VPC etc)
• SQL
• Apache Airflow
• CloudWatch
• REST APIs
• Postman
• Python
• Git & GitHub
• Scripting

• Bachelor’s Degree in Computer Science, Data Science, Engineering or a related field.
• Demonstrated ability to build scalable data models and data pipelines.
• Familiarity with big data tools and environments, coupled with strong problem-solving skills and analytical thinking.