Senior Data Engineer (Azure Databricks)

Applaudo; Lima Metropolitana; On-site; PEN 241,000 - 379,000; Full time

Job summary

Applaudo in Peru is seeking a Senior Data Engineer to design, build, and maintain production-grade data pipelines using Azure Databricks and PySpark. You will connect data across enterprise systems, ingest from APIs, databases, and cloud storage, and ensure data quality.

The role emphasizes ownership, documentation, and collaboration with a US-based team, delivering scalable transformations and reliable datasets to empower business insights.

Qualifications

• 5+ years of professional experience in Data Engineering, designing, building, and maintaining production-grade data pipelines.
• 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 Spark SQL, for processing data at scale.
• Advanced SQL proficiency, including complex transformations, data validation, and query performance optimization.
• Experience integrating data from multiple sources (REST APIs, relational databases, cloud storage, SFTP) and Azure data services.
• Knowledge of data warehousing and dimensional modeling.

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 ingest data from multiple systems.
• Ingest data from APIs, relational databases, cloud storage, and SFTP sources.
• Integrate data from enterprise platforms into a centralized Data Hub and maintain data warehouses.
• Write and optimize SQL transformations, ensure data accuracy and processing efficiency.
• Document pipelines, dependencies, and processes; troubleshoot issues and communicate progress.

Skills

Azure Databricks

Python

Apache Spark

PySpark

SQL

Data warehousing

Dimensional modeling

REST APIs

Relational databases

Cloud storage

SFTP

Azure data services

Data quality checks

Troubleshooting

English communication

Autonomous / ownership

Tools

Azure Databricks

PySpark

Spark SQL

SQL Server

Azure Data Lake

REST API integration

SFTP

Job description

You are a Senior Data Engineer passionate about building scalable, production-grade data pipelines and transforming complex data from multiple sources into reliable, business-ready datasets. You thrive when working with Azure Databricks, Python, and Spark to solve data integration challenges and support enterprise data ecosystems.

You enjoy connecting data across business platforms, optimizing data transformations, and ensuring accuracy and consistency throughout the data lifecycle. You take ownership of your work, ask the right questions early, and proactively communicate risks and blockers. You value clear documentation, technical discipline, and delivering high-quality solutions that support business needs.

You Bring to Applaudo the Following Competencies:

• 5+ years of professional experience in Data Engineering, designing, building, and maintaining production-grade data pipelines.
• 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.

Nice to have:

• Experience migrating SQL-based data workloads to Azure Databricks.

You Will Be Accountable for the Following 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.

Qualifications

• Strong proficiency in Azure Databricks, Python, and Apache Spark.
• Advanced SQL skills and solid knowledge of data warehousing and dimensional modeling.
• Proven experience developing and maintaining production data pipelines.
• Hands-on experience with Microsoft Azure data services and integrating data from multiple enterprise systems.
• Strong understanding of data quality, validation, and consistency across source and target systems.
• Strong ownership, autonomy, documentation, and communication skills.
• Ability to communicate effectively in English and collaborate with a US-based enterprise team.

Additional Information

About Us

We Are Engineered Different.

At Applaudo, talented people design, build, and scale meaningful, AI-powered solutions that create real business impact. As an AI-native organization, we collaborate across design, development, cloud, data, and artificial intelligence to turn ideas into scalable products that transform how companies operate, make decisions, and grow.

We are building a high-performance culture grounded in five values: Empowering Excellence, Collaborative Teamwork, Unsolicited Respect, Consistent Transparency, and Efficient Communication. These define how we work, how we support one another, and how we hold ourselves accountable.

Applaudo is a place for people who want to learn fast, take ownership, and work alongside strong teams they are proud to belong to. Joining us means being part of an organization that is evolving intentionally, investing in modern ways of working, and leading AI-native transformation at scale.