Senior Data Engineer

You will be responsible for architecting and building robust data pipelines, data contracts, and processing frameworks that power analytics and ML features across Foodics. You ll work closely with ML Engineers and platform teams to ensure the reliability, scalability, and governance of our data infrastructure.

What Will You Do

• Design and implement scalable ETL/ELT pipelines using cloud-native tools.
• Define and enforce data contracts with domain squads and internal consumers.
• Collaborate with ML Engineers on feature engineering and model-ready datasets.
• Build monitoring, alerting, and observability into the data infrastructure.
• Ensure data security, lineage, and compliance with internal standards.
• Contribute to onboarding toolkits and reusable data components.

What Are We Looking For

• 5+ years of experience in data engineering, with a track record in scalable pipelines.
• Strong command of Python, SQL, and orchestration tools (e.g., Airflow, AWS Glue, Step Functions).
• Experience with modern Lakehouse architecture and tools (e.g., S3, Redshift, Snowflake, dbt).
• Deep understanding of data modeling, lineage, observability, and governance frameworks. (e.g., dimensional modeling, normalized vs. denormalized structures, schema evolution, ML feature stores)
• Familiarity with ACID-compliant data formats such as Apache Iceberg, Delta Lake, or Apache Hudi, and experience managing large-scale datasets with time travel, schema evolution, and transactional guarantees.
• Experience building fault-tolerant, testable, and maintainable pipelines in production environments.
• Proven ability to work in cross-functional teams, collaborating with ML Engineers, Analysts, and Product Managers.
• Familiar with CI/CD and infrastructure-as-code (Terraform/CDK preferred).
• Strong communication skills and a mindset focused on documentation, standards, and continuous improvement.

Who Will Excel

• Candidates with knowledge of MLOps integration and streaming technologies (e.g., Kafka, Kinesis).