Data Engineer
Design, build, and optimize robust data pipelines to create scalable, high-value data products. Collaborate with business stakeholders and engineering teams to bridge technical data architecture with business applications.
Remote Data Engineer Jobs in Peru
57 Data Engineer jobs in Peru available for remote work from home. Apply for positions such as Data Engineer, Senior Data Engineer, #8 Data Engineer Senior - Databricks - Latam and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Design, build, and optimize robust data pipelines to create scalable, high-value data products. Collaborate with business stakeholders and engineering teams to bridge technical data architecture with business applications.
Develop and optimize enterprise ETL/ELT pipelines with Talend and Apache Spark, and write performant SQL for large-scale datasets. Collaborate with solution architects on governance, schema management, and data quality, while troubleshooting distributed jobs and documenting work within an Agile team.
The role involves co-developing batch and streaming data pipelines on Databricks and defining data contracts and quality rules. You will also mentor domain engineers on data product ownership and best engineering practices.
You will design and build a multi-source data platform for concurrent ingestion, event-driven processing, and orchestrated batch workflows. Additionally, you will own the platform end-to-end, from architecture and ingestion through production operations.
Build and maintain automated ETL pipelines to integrate marketing platforms and CRMs into a central database. Develop and manage data dashboards while automating recurring business reports and analyzing performance metrics.
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Design, build, and manage scalable multi-cloud data platforms while developing real-time and batch data pipelines. Ensure high standards of data reliability, security, and governance while mentoring engineering team members.
Design, build, and maintain data pipelines and analytics solutions using Databricks and Python. Collaborate with IT teams to implement data governance standards and support Power BI reporting.
You will build and maintain ETL pipelines between Zuora REST APIs and a GCP data warehouse while managing transformation logic for billing and subscription data. Additionally, you will implement pipeline monitoring, error handling, and data-quality controls to ensure reliable data movement.
The Data Engineer designs, builds, and maintains scalable data infrastructure and ETL pipelines to support digital marketing strategies. They ensure data integrity and quality while collaborating with cross-functional teams to prepare data for dashboards and reporting.
Own and develop the company’s analytics infrastructure, including data collection, ETL/ELT pipelines, orchestration, backfills, monitoring, and integrations with marketing, billing, product, and internal data sources. Build and maintain dbt models, implement data quality controls, and document data sources, models, and business logic for analytics teams.
You will design and scale robust data architecture to support analytics, experimentation, and decision-making across the company. You will also lead data quality initiatives and collaborate with cross-functional teams to build scalable data systems.
Design, develop, and maintain batch and event-driven data pipelines while optimizing IBM DB2 database performance. Collaborate with cross-functional teams to integrate legacy systems with modern cloud platforms and ensure data reliability.
Design, build, and maintain scalable batch and streaming data pipelines, transforming data from diverse sources into governed, analytics-ready datasets and reusable data services. Collaborate with clients, analysts, data scientists, and architects to ensure data quality, security, governance, performance, and clear technical documentation.
The Senior Data Engineer will design, develop, and maintain scalable ETL/ELT pipelines while managing AWS workflows and orchestration tools. Additionally, the role involves leading a small team, collaborating with cross-functional stakeholders, and implementing AI-driven automation for engineering tasks.
Lead and mentor a team of data engineers while setting technical direction and driving engineering excellence. Own the end-to-end architecture, design, and implementation of scalable data platforms and migration strategies.
The Data Engineer will design, build, and maintain scalable data pipelines and ETL/ELT processes to integrate multiple data sources. They will also ensure data quality and collaborate with cross-functional teams to support analytics and data-driven decision-making.
Design, develop, and optimize scalable data pipelines using Azure Data Factory and other cloud-native services. Implement secure data migration strategies, including encryption and masking, while ensuring reliable performance across Azure environments.
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You will architect and lead the development of large-scale data pipelines and streaming systems to process billions of daily events. Additionally, you will own production data systems, ensuring high uptime, reliability, and scalability while collaborating with cross-functional teams.
Design, develop, and maintain scalable ETL/ELT data pipelines and cloud-native data solutions using Python, PySpark, and Snowflake. Collaborate with cross-functional teams to optimize data performance, ensure data quality, and implement robust data governance practices.
Design and build scalable data pipelines to support machine learning workflows, including feature engineering and real-time data ingestion. Collaborate with cross-functional teams to ensure data quality, monitoring, and efficient model deployment.
Design and build scalable data pipelines while optimizing transformation workflows in Snowflake or Databricks. Collaborate with cross-functional teams to ensure high-quality, performant, and secure data systems for analytics and reporting.
The roles involve designing, building, and maintaining scalable data pipelines, cloud infrastructure, and analytical dashboards to support business decision-making. Responsibilities also include ensuring data quality, automating infrastructure, and collaborating across technical and business teams.
The role involves designing, developing, and maintaining reliable production-grade ETL/ELT pipelines while ensuring data quality and consistency. You will collaborate in an agile environment to investigate system issues, perform root-cause analysis, and support critical data engineering activities.
Design, build, and optimize complex data models and graph structures within SAP HANA Cloud to support enterprise-level applications. Collaborate with machine learning and search engineering teams to ensure efficient data pipelines and high-performance query execution.
Develop and maintain scalable data pipelines and models to support cybersecurity, GRC, and AI-assisted workflows. Collaborate with cross-functional teams to ensure data reliability, audit readiness, and effective integration with enterprise platforms.
Lead and mentor data engineering teams while setting technical direction and driving engineering excellence. Own the end-to-end architecture, design, and implementation of scalable data platforms and migration strategies.
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The role involves designing, building, and maintaining scalable BigQuery datamarts and analytical tables to support BI reporting. You will also develop data pipelines and transformation workflows while ensuring data quality and governance across the environment.
You will design, develop, and maintain scalable data pipelines and ETL/ELT processes while modernizing legacy infrastructure. Additionally, you will collaborate with the analytics team to deliver effective data solutions and ensure the reliability and performance of the data platform.
Design, build, and maintain scalable data pipelines and cloud data solutions using Snowflake. Collaborate with engineering and analytics teams to ensure high-quality data availability for reporting and decision-making.
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