Wakapi
Data Engineer (Core & Analytics)
Wakapi is hiring a Data Engineer in Argentina to build resilient Python ETL pipelines using Medallion architecture, manage PostgreSQL and SQLite databases, and create cloud-portable data lakes with open formats (Parquet, Iceberg, Delta Lake), leveraging DuckDB for embedded analytics and Databricks/Spark for distributed compute.
- Compensation
- Not disclosed
- Location
- Argentina
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Advanced SQL proficiency with deep PostgreSQL expertise
- Working knowledge of SQLite
- Hands-on experience building robust analytical pipelines using Python and DuckDB
- Mastery of open table and storage formats (Parquet, Apache Iceberg, Delta Lake)
- Proven track record designing data lakes using the Medallion data processing architecture
Nice to have
- Familiarity with the Databricks / PySpark ecosystem for distributed processing
Full description
The Role
Builds performant data processing pipelines, manages relational databases, and constructs cloud-portable data lake environments using modern open storage formats and embedded analytical engines.
Responsibilities
- Pipeline Design: Construct resilient data processing pipelines in Python using Medallion architecture principles (Bronze/Silver/Gold) to transform raw data into analytics-ready assets.
- Open Storage Management: Standardize data storage using open formats including Parquet, Apache Iceberg, and Delta Lake to ensure cross-cloud compatibility.
- Embedded Analytics: Leverage DuckDB integrated with Python for fast, lightweight, and performant localized data processing within ETL workflows.
- Database Operations: Architect and optimize production PostgreSQL schemas while utilizing SQLite for embedded or lightweight localized storage needs.
- Distributed Compute: Scale heavy ETL, data transformation, and analytics workloads using Databricks or Apache Spark.
Requirements
- Advanced SQL proficiency with deep PostgreSQL expertise and working knowledge of SQLite.
- Hands‑on experience building robust analytical pipelines using Python and DuckDB.
- Mastery of open table and storage formats (Parquet, Apache Iceberg, Delta Lake).
- Proven track record designing data lakes using the Medallion data processing architecture.
- Familiarity with the Databricks / PySpark ecosystem for distributed processing.
Python & SQL | PostgreSQL & SQLite | Medallion Architecture | DuckDB | Parquet / Iceberg / Delta | Databricks / Spark
C - PGS - 29092026