Senior Bi & Data Analytics Engineer

Kavak; Ciudad de Mendoza; On-site; ARS 1,200,000 - 2,300,000; Full time

Job summary

Kavak is seeking a data engineer to build and optimize data pipelines, manage PostgreSQL schemas, and design cloud-friendly data lake environments using Parquet, Iceberg, and Delta Lake. You will integrate DuckDB with Python for embedded analytics within ETL workflows and work with SQLite for lightweight storage needs.

The role emphasizes developing scalable ETL processes and leveraging Databricks or Apache Spark for distributed compute across data platforms.

Qualifications

• Advanced SQL proficiency with deep PostgreSQL expertise.
• 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.

Responsibilities

• Pipeline Design: Construct resilient data processing pipelines in Python using Medallion architecture principles to transform raw data into analytics-ready assets.
• Open Storage Management: Standardize data storage using open formats including Parquet, Apache Iceberg, and Delta Lake for cross-cloud compatibility.
• Embedded Analytics: Leverage DuckDB integrated with Python for fast local data processing within ETL workflows.
• Database Operations: Architect and optimize production PostgreSQL schemas and use SQLite for embedded or lightweight storage.
• Distributed Compute: Scale ETL and analytics workloads using Databricks or Apache Spark.

Skills

Python

Advanced SQL

Tools

PostgreSQL

SQLite

DuckDB

Parquet

Apache Iceberg

Delta Lake

Job 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.