Data Engineer

Data Engineer

• Location: Argentina — Remot
• Type: Full-time, long-term contractor
• Eligibility: This opportunity is open exclusively to candidates based in Argentina.

About The Company

Our client is a leading cloud-first consulting company delivering Managed Services, Staffing, and Professional Services. With a remote-first global team across North America, Europe, and Southeast Asia, the company helps organizations embrace cloud technologies through innovative, customer-focused solutions.

The organization values collaboration, agility, innovation, integrity, diversity and inclusion, and offers an environment where talented professionals can work on meaningful, cutting-edge initiatives.

About The Role

Our client is looking to hire a highly skilled Data Engineer to design, build, and operate scalable AWS data platforms supporting analytics, batch and streaming pipelines, and AI/ML workloads.

This role requires strong hands-on AWS and Python expertise, as well as the ability to build reliable data systems, integrate enterprise platforms, and improve data accessibility, governance, and quality across the organization.

What You'll Do

• Design, build, and maintain scalable AWS data platforms aligned with AWS Well-Architected best practices.
• Develop and operate batch and streaming data pipelines for analytics and AI/ML use cases.
• Build ingestion, transformation, enrichment, and normalization workflows using internal systems and external APIs.
• Work with structured, semi-structured, unstructured, and graph data.
• Design and maintain data models, including normalized, denormalized, and graph-based models.
• Build and maintain knowledge graphs that enable advanced analytics and inference.
• Integrate data from CRM and ERP platforms such as Salesforce, HubSpot, SAP, NetSuite, Dynamics 365, and Workday.
• Establish data governance practices around cataloging, lineage, access control, encryption, and auditability.
• Implement data-quality, observability, and monitoring processes for freshness, completeness, and pipeline health.
• Optimize data architecture for cost and performance through partitioning, indexing, compression, and storage tiering.
• Create internal tools, dashboards, and technical documentation to improve visibility and maintainability.

What We're Looking For

• 4+ years of experience designing and operating AWS data platforms.
• Strong hands-on experience with AWS services such as S3, Glue, Lake Formation, Athena, Redshift, EMR, Kinesis/MSK, DynamoDB, OpenSearch, and Neptune.
• Strong Python skills, with an emphasis on modular, testable, and maintainable code.
• Advanced SQL skills, including CTEs, window functions, and query optimization.
• Experience with ETL/ELT, data warehouses, lakehouse architectures, and analytical query engines.
• Experience with Spark, Hadoop, Hive, and/or Flink.
• Strong understanding of distributed data systems, event-driven architectures, fault tolerance, and idempotency.
• Experience with API integrations and enterprise CRM/ERP systems.
• Experience with CloudWatch, CloudTrail, data governance, security, and compliance practices.
• Familiarity with Terraform or CloudFormation.
• Advanced English communication skills and the ability to explain technical trade-offs to technical and non-technical stakeholders.