Remote Dcs & Data Analytics Engineer (Sql/Power Bi)

Dev PRO; Ciudad de Mendoza; Remote; ARS 139,086,000 - 185,448,000; Full time

Job summary

Dev PRO in Argentina is seeking an experienced data engineer to design and optimize end-to-end data pipelines and analytics assets. You will work with Medallion architecture, open formats like Parquet, Iceberg, and Delta Lake, and leverage Python with DuckDB for in-stream processing.

The role emphasizes scalable PostgreSQL schema design and efficient embedded storage using SQLite, with distributed processing on Databricks or Spark to handle large ETL workloads.

Qualifications

• Advanced SQL with deep PostgreSQL expertise and SQLite knowledge.
• Hands-on experience building analytical pipelines in Python using 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 and PySpark ecosystem for distributed processing.

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, 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 storage needs.
• Distributed Compute: Scale heavy ETL, data transformation, and analytics workloads using Databricks or Apache Spark.

Skills

SQL

Python

DuckDB

PostgreSQL

SQLite

Tools

Parquet

Apache Iceberg

Delta Lake

Databricks

PySpark

Spark

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.