Senior Data Engineer: Azure Databricks & Spark Specialist

Applaudo; Ciudad de México; On-site; MXN 900,000 - 1,400,000; Full time

Job summary

Applaudo is seeking a Senior Data Engineer who loves building scalable, production-grade data pipelines and turning diverse data into reliable, business-ready datasets. You will work with Azure Databricks, Python, and Spark to solve data integration challenges across enterprise ecosystems.

You will own the data lifecycle, ensure data quality and consistency, document pipelines, and collaborate with a US-based team to deliver high-impact data solutions spanning CRM, marketing, retail, and

Qualifications

• 5+ years of professional experience in Data Engineering.
• Strong hands-on experience with Azure Databricks.
• Advanced Python skills for data processing, transformation, and pipeline development.
• Solid experience with Apache Spark, including PySpark and/or Spark SQL, for processing data at scale.
• Advanced SQL proficiency, including complex transformations, data validation, and query performance optimization.
• Strong knowledge of data warehousing and dimensional modeling, including facts, dimensions, and data marts.
• Experience integrating data from multiple sources, including REST APIs, relational databases, cloud storage, and SFTP.
• Hands-on experience with Microsoft Azure data services for data ingestion, storage, processing, and integration.
• Experience implementing data quality checks and validating consistency between source systems and target data models.
• Ability to troubleshoot pipeline failures, investigate data discrepancies, and implement reliable solutions.
• Strong problem-solving, analytical, and organizational skills.
• Ability to work autonomously, take ownership, and follow established engineering practices and documentation standards.
• Strong English communication skills, with the ability to collaborate effectively with a US-based team.

Responsibilities

• Design, build, and maintain reliable, production-grade data pipelines using Azure Databricks and Python.
• Develop scalable data transformations using PySpark or Spark SQL to integrate data from multiple business systems.
• Ingest and process data from APIs, relational databases, cloud storage, and SFTP sources.
• Integrate data from ticketing, CRM, marketing, retail, and other enterprise platforms into a centralized Data Hub.
• Develop and maintain data warehouse structures, dimensional models, and data marts aligned with business requirements.
• Write, optimize, and maintain SQL transformations to ensure data accuracy and processing efficiency.
• Implement data quality validations and consistency checks between source systems and target models.
• Build and maintain outbound data feeds for third-party systems according to defined specifications.
• Investigate data discrepancies, troubleshoot pipeline issues, and implement appropriate corrective actions.
• Document data pipelines, transformation logic, dependencies, and technical processes.
• Collaborate with team members and stakeholders to clarify requirements, identify risks early, and deliver reliable data solutions.
• Communicate progress, blockers, and potential delays proactively, proposing clear next steps to keep deliverables on track.

Skills

Azure Databricks

Python

Apache Spark

Spark SQL

PySpark

SQL

Data warehousing

Dimensional modeling

REST APIs

Relational databases

Cloud storage

SFTP

Azure data services

Data quality

Troubleshooting

Documentation

Communication

English

Tools

Azure Databricks

Python

Apache Spark

PySpark

Spark SQL

SQL

Azure

Job description

Applaudo is seeking a Senior Data Engineer who loves building scalable, production-grade data pipelines and turning diverse data into reliable, business-ready datasets. You will work with Azure Databricks, Python, and Spark to solve data integration challenges across enterprise ecosystems.

You will own the data lifecycle, ensure data quality and consistency, document pipelines, and collaborate with a US-based team to deliver high-impact data solutions spanning CRM, marketing, retail, and