Data Engineering -- Modeller,Ingestion,App engineer

Market Cloud Ltd; Monterrey; Presencial; MXN 600.000 - 900.000; Jornada completa

Descripción de la vacante

Market Cloud Ltd is seeking an experienced Data Engineer in Monterrey to design scalable data models, build data pipelines and ingestion solutions for analytics and business applications.

You will collaborate with BI, data scientists and developers to deliver reliable data architectures, implement CDC, ensure data quality and governance, and document pipelines and models.

Formación

• Extensive experience in data modelling across conceptual, logical and physical layers.
• Hands-on SQL with relational databases and data warehousing.
• Proficient in Python, Java or Scala for data processing.
• Experience designing and implementing ETL/ELT pipelines and data ingestion.

Responsabilidades

• Design conceptual, logical, and physical data models for analytics and operations.
• Create scalable relational and dimensional data models, star/snowflake schemas.
• Develop fact and dimension tables and data marts with performance in mind.
• Design and develop robust ETL/ELT pipelines for batch and real-time ingestion.
• Ingest data from databases, APIs, files, and cloud platforms; ensure data quality.
• Develop data-driven applications and APIs; ensure security and governance.

Conocimientos

Data Engineering

Data Modelling

Data Ingestion

ETL/ELT

SQL

Python

Java

Scala

APIs

Data Warehouses

Data Lakes

Data Governance

Data Quality

Security

Documentation

Descripción del empleo

Experience: 5–7 Years

Location : Monterrey

Employment Type: Contract

Role Overview

We are looking for an experienced Data Engineer with strong expertise across Data Modelling, Data Application Engineering, and Data Ingestion. The candidate will be responsible for designing scalable data models, developing data applications and pipelines, and building reliable data ingestion solutions to support analytics, reporting, and business applications.

Key Responsibilities

• Design and develop conceptual, logical, and physical data models.
• Create scalable relational and dimensional data models for analytical and operational requirements.
• Develop fact and dimension tables, star/snowflake schemas, and data marts.
• Optimize data structures, queries, and database performance.
• Ensure data quality, consistency, integrity, and governance.
• Work closely with business and technical teams to understand data requirements.

Data Ingestion Engineering

• Design and develop robust ETL/ELT pipelines for batch and real-time data ingestion.
• Ingest data from databases, APIs, files, cloud platforms, and third-party applications.
• Develop scalable and fault-tolerant data pipelines.
• Implement data validation, transformation, cleansing, and error-handling mechanisms.
• Monitor pipeline performance and troubleshoot data ingestion issues.
• Implement incremental data loading and change-data-capture (CDC) processes where required.

Data Application Engineering

• Develop data-driven applications and services that consume and process enterprise data.
• Build APIs and backend services for data access and integration.
• Develop reusable data processing components and services.
• Integrate data applications with databases, data warehouses, APIs, and cloud platforms.
• Support application performance, scalability, reliability, and security.
• Collaborate with application developers, data scientists, analysts, and architects.

Technical Skills

Mandatory:

• Strong experience in Data Engineering and Data Modelling.
• Hands-on experience with SQL and relational databases.
• Strong programming experience in Python, Java, or Scala.
• Experience with data warehouses and data lakes.
• Knowledge of data integration and API-based ingestion.
• Strong understanding of data quality, governance, and security.
• Scalable and optimized data models.
• Reliable batch and real-time data ingestion pipelines.
• High-quality and governed datasets.
• Data-driven applications and APIs.
• Improved data processing performance and reliability.
• Comprehensive technical documentation for data pipelines, models, and applications.