Senior Data Engineer – AWS, RAG Pipelines

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Jalasoft

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2003

☁️ SaaS

📚 Education

Software Development • SaaS • Education

Jalasoft is a global nearshore software development company with a strong presence across 70 cities in 13 countries. With a team of over 1000 South American-based software engineers, Jalasoft specializes in software development, quality assurance (QA), and DevOps solutions. The company focuses on staff augmentation and dedicated teams tailored to meet client needs, ensuring quality and efficiency in project delivery. Jalasoft places a strong emphasis on security, holding an ISO 27001 certification, and partners with leading technology firms like Palo Alto, NVIDIA, and Cisco to offer reliable network and data center management. In addition, Jalasoft operates Jala University, offering educational programs in technology to foster and recruit top tech talent. The company aims to drive digital transformation by providing agile, culturally aligned nearshore software solutions.

📋 Description

• Design and operate the cloud data infrastructure powering AI initiatives. • Architect production-scale data lakes on AWS. • Build real-time ingestion and observability pipelines. • Own the vector search and embedding layers that feed RAG systems and autonomous agents.

🎯 Requirements

• Overall Experience: 7+ years in Data Engineering, Distributed Systems, or Data Architecture • AWS & Infrastructure: 4+ years architecting production-scale data lakes, storage tiers, and event streaming • AI/LLM Pipelines: 2+ years building RAG systems, managing embeddings, and orchestrating foundational models • Proficiency in AWS Data Lake Architecture & Storage • Proficiency in Real-Time Observability & Log Analytics • Proficiency in Elasticsearch & OpenSearch Optimization, Vectorization, Embeddings • Proficiency in Amazon Bedrock & Generative AI Pipelines • Proficiency in Software Engineering & API Ingestion • Production-level proficiency in one or more of: C# (.NET Core), Java, Python, or Node.js • AWS S3 partitioning strategies, lifecycle policies, and columnar formats (Parquet, Iceberg) • AWS Glue Data Catalog and Lake Formation for multi-tenant, fine-grained access control • Query optimization over petabyte-scale datasets using Amazon Athena and Redshift Spectrum • Distributed oTel collector configuration for log, trace, and metrics capture and routing into S3 • High-volume streaming of system logs, Datadog captures, and raw server events into S3 • Real-time CDC from PostgreSQL using Debezium or AWS DMS • Amazon OpenSearch clusters with simultaneous lexical and high-dimensional vector search • OpenSearch index lifecycle management, sharding strategies, and dynamic mappings at scale • Amazon Bedrock foundational model APIs (Claude, Titan) for data enrichment, classification, and semantic parsing • Knowledge Bases for Amazon Bedrock for automatic chunking, metadata extraction, and vector index syncs from S3 • ETL/ELT pipelines ingesting unstructured event data from SaaS APIs (e.g., Pendo, Hotjar, Google Analytics) • MCP server development to expose data lake context and utilities to AI agents

🏖️ Benefits

• Remote work. • 13 floating holiday. • 15 vacation days per year completed. • Good working environment.