Senior Data Engineer
Design and build scalable, reliable data platforms using Azure Databricks and Delta Lake. Collaborate with cross-functional teams to turn business requirements into efficient data pipelines and models.
Remote Data Engineer Jobs in Argentina
76 Data Engineer jobs in Argentina available for remote work from home. Apply for positions such as Senior Data Engineer, Data Engineer, Freelance Senior Quantexa Data Engineer and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Design and build scalable, reliable data platforms using Azure Databricks and Delta Lake. Collaborate with cross-functional teams to turn business requirements into efficient data pipelines and models.
The Data Engineer will design and maintain robust ETL pipelines and optimize relational databases to support business intelligence. They will also develop interactive Power BI dashboards and ensure data integrity through rigorous validation and reconciliation.
Design, develop, and implement complex software solutions using the Quantexa platform. Collaborate with cross-functional teams to ensure high performance, scalability, and reliability of software deliverables.
You will be responsible for building and maintaining data models, Clickhouse aggregations, and event-driven streaming applications to support internal analytics and product features. Additionally, you will harden the Kafka ecosystem and develop data lake architectures for long-term storage and disaster recovery.
Build and maintain scalable data pipelines using Azure Databricks, PySpark, and SQL while developing Bronze, Silver, and Gold data layers. Collaborate with cross-functional teams to implement data validation, quality checks, and production-ready analytics solutions.
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You will design and own a multi-source data platform, managing everything from architecture and ingestion to production operations. Responsibilities include building robust data pipelines, orchestrating workflows, and implementing data quality monitoring.
Design, build, and manage scalable multi-cloud data platforms while developing real-time and batch data pipelines. Drive technical architecture, mentor engineering staff, and ensure high standards for data reliability and security.
Lead the migration of data into a modern Databricks/Azure architecture while designing and optimizing scalable data pipelines. Collaborate with global stakeholders to ensure data quality, security, and effective reporting enablement.
You will own data engineering projects end-to-end, collaborating with Product Managers to define requirements and implement scalable solutions. Additionally, you will focus on system performance and stability while participating in code reviews to ensure high-quality, maintainable code.
The role involves co-developing batch and streaming pipelines on Databricks while defining data contracts and quality rules. Additionally, the engineer will mentor domain teams on data modeling and best practices to improve platform templates and tooling.
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 own and evolve scalable data ingestion pipelines while ensuring data reliability and quality across the ecosystem. Additionally, you will collaborate with cross-functional teams to solve complex identity resolution challenges and maintain robust event-driven data workflows.
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.
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.
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.
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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.
The Data Engineer will design, build, and maintain automated data pipelines using Snowflake and Azure Data Factory. They will also be responsible for transforming data with dbt and ensuring high data quality and system performance.
You will design and build production-ready Agentforce agents, including defining topics, actions, and guardrails. Additionally, you will implement data retrieval strategies and perform rigorous evaluation and testing to ensure agent reliability.
You will build and maintain the data foundation for Salesforce Data 360 and Agentforce by ingesting, harmonizing, and modeling data from various sources. Additionally, you will design identity resolution rulesets and implement transformation pipelines while ensuring data observability and cost optimization.
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.
Own the data platform from architecture through production, building concurrent ingestion and orchestrated batch and event-driven workflows for data from APIs, webhooks, files, and web scraping. Establish raw-to-curated data layers, reliable recovery and replay, data quality monitoring, and optimized PostgreSQL delivery, while integrating enrichment and LLM-based extraction.
Design, build, and maintain scalable AWS data pipelines and optimized ETL processes using PySpark and SQL, while collaborating with stakeholders to deliver reliable data solutions. Monitor and tune pipeline performance, ensure data quality and governance, document workflows, and resolve second-level incidents.
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.
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Design and maintain robust data pipelines, ELT processes, and data warehouse architecture to support financial operations. Implement automated data orchestration and ensure data integrity through proactive monitoring and alerting.
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.
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.
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