Senior Data Engineer – AI/ML
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Job Description
Data Engineer for iFood's AI/ML Platforms, collaborating on data solutions and managing robust data pipelines. Join a leading Latin American tech company focused on innovation in food delivery, fintech and more.
Responsibilities:
- Collaborate with stakeholders across multiple companies in the iFood ecosystem to map data systems, define ingestion strategies, and coordinate secure, governed data sharing for collaborative AI projects.
- Design, build, and operate reliable batch and streaming pipelines that ingest, transform, and store large volumes of structured and unstructured data on platforms such as AWS S3.
- Define and manage data access policies and controls, ensuring secure and appropriate access to datasets across platforms (AWS S3, Databricks) aligned with governance and compliance requirements.
- Implement data quality frameworks and validation checks tailored to each data source in the ecosystem.
- Develop and apply best practices for organization, cataloging, and comprehensive metadata management optimized for efficient training of LLMs and for analytics.
- Build and manage ETL/ELT workflows using distributed computing frameworks such as Spark on Databricks or Amazon EMR.
- Monitor, analyze, and proactively optimize costs associated with data storage, processing, and transfer across the platform.
- Troubleshoot pipeline issues, optimize queries, and document solutions to enable team autonomy.
Requirements:
- Languages: Advanced Python and SQL with strong development experience.
- Big Data: Proficiency in Spark (Databricks/EMR) and knowledge of Ray.
- Cloud: Strong experience with AWS (primary); knowledge of GCP is a plus.
- Databases: Experience with relational databases and NoSQL (MongoDB).
- Concepts: Expertise in ETL/ELT and data modeling for production environments.
- Experience: Solid background in data engineering with a focus on production readiness and reliability.
- Direct experience supporting multiple external clients or business units in complex environments.
- Knowledge of workflow orchestration tools (Airflow, Prefect, Luigi) for automation of processes.
- Experience with graph databases (Neo4j, Amazon Neptune) for advanced relationship modeling.
- Knowledge of containerization and Kubernetes for scalable data workloads.
Benefits:
- We do not discriminate on the basis of disability, gender, sexual orientation, race/ethnicity, age, national origin, family status, or appearance.
- We have voluntary employee groups (foodlovers) that discuss topics such as race, gender, LGBTQI+, and people with disabilities.
- We work in a highly dynamic and versatile environment.
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