Bilingual Power Bi & Sql Analytics Engineer

Gbs Group; Ciudad de Mendoza; On-site; ARS 123,554,000 - 185,331,000; Full time

Job summary

1801 Haleon Argentina S.A. is seeking a data engineering specialist to build high-performance data pipelines in Python and implement Medallion (Bronze/Silver/Gold) architectures.

You will standardize storage with Parquet, Iceberg, and Delta Lake to enable cross-cloud analytics, and use DuckDB for fast localized processing within ETL workflows. The role also involves PostgreSQL schema design and scalable processing on Databricks or Spark.

Qualifications

• Advanced SQL proficiency with PostgreSQL expertise.
• Experience building analytical pipelines in Python.
• Knowledge of open table/storage formats (Parquet, Iceberg, Delta Lake).
• Experience with Medallion data architecture (Bronze/Silver/Gold).
• Familiarity with Databricks / PySpark for distributed processing.

Responsibilities

• Design robust data pipelines in Python following Medallion architecture to transform raw data into analytics-ready assets.
• Standardize data storage using Parquet, Iceberg and Delta Lake for cross-cloud compatibility.
• Leverage DuckDB with Python for fast local data processing within ETL workflows.
• Architect and optimize PostgreSQL schemas; support lightweight SQLite storage needs.
• Scale ETL and analytics workloads using Databricks or Apache Spark.

Skills

SQL

PostgreSQL

SQLite

Python

DuckDB

Parquet

Apache Iceberg

Delta Lake

Databricks

PySpark

Medallion architecture

Tools

Parquet

Apache Iceberg

Delta Lake

DuckDB

Databricks

PySpark

Spark

PostgreSQL

SQLite

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.