ETL Developer

Merkleinnovation; Asia; Presencial; PEN 60.000 - 90.000; Jornada completa

Descripción de la vacante

Merkleinnovation is seeking a skilled ETL Development Engineer with hands-on experience building high-throughput data pipelines using PySpark. You will design, develop, and optimize scalable data warehouse models and Spark-based ETL workflows, collaborating with cross-functional teams to ensure data availability and reliable delivery.

The role emphasizes performance tuning of Spark jobs, DAG orchestration with Airflow, and adherence to coding standards, documentation, and testing.

Formación

• 3+ years PySpark offline ETL development experience.
• Strong Spark Core/SQL tuning and Airflow orchestration.
• Data warehouse modeling with dimensional modeling experience.
• Familiarity with cloud environment workflows and Telco data processing.
• Independent delivery with strong coding standards.
• Experience migrating from legacy ETL systems (Ab Initio) to PySpark.
• Data mapping and large-scale migrations in Telco/Banking sectors.

Responsabilidades

• ETL Pipeline Development: design, build, and maintain high-throughput offline batch ETL pipelines using Spark.
• Performance Tuning: optimize Spark jobs, memory, and query execution for performance and cost efficiency.
• Data Warehouse Modeling: architect scalable dimensional models for analytical workflows.
• Pipeline Orchestration: manage DAG workflows using Airflow with monitoring and alerts.
• Code Quality & Best Practices: ensure clean code, documentation, reviews, and unit testing.
• Migration & Modernization: participate in or lead ETL re-engineering and platform migrations.
• Cross-functional Collaboration: read docs and communicate with international teams in English.

Conocimientos

PySpark

ETL development

Performance tuning

Data warehouse modeling

Pipeline orchestration

Code quality

Migration & modernization

Cross-functional collaboration

English communication

Educación

Bachelor's degree in Computer Science or related field

Herramientas

Apache Spark

Airflow

Descripción del empleo

We are looking for a skilled and self-motivated ETL Development Engineer with strong hands-on experience in high-throughput data pipelines and offline batch processing. In this role, you will design, develop, and optimize scalable data warehouse models and Spark-based ETL workflows. You will work closely with cross-functional teams to ensure high data availability, seamless task orchestration, and reliable data architecture delivery.

Responsibilities

• ETL Pipeline Development: Design, build, and maintain high-throughput offline batch ETL pipelines utilizing Apache Spark (Core/SQL).
• Performance Tuning: Troubleshoot, benchmark, and optimize Spark jobs, memory allocation, and query execution for high performance and cost efficiency.
• Data Warehouse Modeling: Architect and implement scalable data warehouse dimensional models (Kimball/Inmon methodologies, ODS/DWH/ADS layering) supporting analytical workflows.
• Data Warehouse Modeling: Architect and implement scalable data warehouse dimensional models (Kimball/Inmon methodologies, ODS/DWH/ADS layering) supporting analytical workflows.
• Pipeline Orchestration: Manage DAG workflows, incremental processing, failure retry logic, and real-time monitoring/alerting using orchestration platforms such as Apache Airflow.
• Code Quality & Best Practices: Maintain high software engineering standards through clean code writing, robust documentation, code reviews, and automated unit testing.
• Migration & Modernization: Assist in or lead large-scale ETL re-engineering, platform migrations, and optimization initiatives across legacy and modern data stacks.
• Cross-functional Collaboration: Read technical documentation, communicate seamlessly with international tech teams in English, and deliver features independently from requirements to production.

Requirements

• Bachelor's degree or above in a computer-related major
• Experience: 3+ years in PySpark offline ETL development
• Technical Skills: Spark Core/SQL tuning, Airflow orchestration, and data warehouse modeling.
• Domain & Infra: Experience or familiarity with cloud environment workflows and telco data processing challenges.
• Delivery: Strong coding standards and proven independent delivery capability.
• Language: Working proficiency in English (technical documentation, written, and spoken).
• Preferred: Prior experience in large-scale ETL migration or reengineering in telco/cloud environments.
• Proven hands-on experience in executing end-to-end data and logic-level migrations from legacy ETL systems (specifically Ab Initio) to modern frameworks using PySpark
• Strong background in complex data mapping, table design, and script rewriting, preferably within large-scale Data Migration projects in the Telecommunications or Banking sectors

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