What is this position about? We're looking for a Data Engineering Manager to lead the design and delivery of complex data pipelines and integration solutions that power critical business workflows for our clients. You will own end-to-end data engineering initiatives from discovery and POC development through production deployment and optimization, while building and scaling a high-performing engineering team. Your work will span platform-agnostic data architecture, high-volume record matching, deduplication, and near-real-time delivery systems. You will guide teams through complex data modeling decisions, performance optimization, and integration design, helping clients understand the tradeoffs between batch and real-time approaches, API-driven versus clean-room workflows, and infrastructure options. What You Will Do - Design and implement data ingestion architectures on Snowflake. - Lead data engineering projects end to end—from discovery and requirements through POC validation to production deployment—while building and mentoring a high-performing engineering team - Design platform-agnostic data pipelines and schemas that scale reliably at high volume, including complex data modeling for submit-grade-return workflows, identity graphs, record matching, and deduplication systems - Own discovery pipeline initiatives and functional POCs, implementing high-volume matching logic and conducting comprehensive performance, load, and scale testing to validate architectural decisions - Assess and optimize latency, throughput, connection stability, and integration options including APIs, batch delivery, and governed clean-room workflows - Define data integration strategies and communicate tradeoffs clearly to clients, guiding infrastructure and tool selection based on performance requirements and business constraints - Lead partner-facing API design and integration strategy,



architecting batch versus real-time decisions and designing governed clean-room solutions for partner data exchange - Establish technical standards for schema design, SQL quality, pipeline development, and production readiness across the team through reviews, mentoring, and knowledge sharing What We Are Looking For - 7+ years of hands-on data engineering experience, with proven expertise in building and deploying high-volume data pipelines in production - 2+ years of direct team leadership or technical management experience - Advanced SQL proficiency with deep expertise in schema and data-model design, complex joins, and performance optimization - Proven track record with high-volume record matching, deduplication, and identity resolution systems - Strong experience with platform-agnostic data engineering—ability to assess and implement solutions across Snowflake, Databricks, BigQuery, Redshift, and other platforms - Demonstrated expertise in pipeline development, performance testing, latency and throughput analysis - Experience designing and implementing batch and real-time data integration workflows - Knowledge of governed clean-room solutions and data governance practices - Solid understanding of API design, microservices patterns, and event-driven architectures - A clear communicator equally comfortable with engineering teams and senior stakeholders - Strong hiring and team-building instincts with proven mentoring experience What about languages?

- English: Advanced (required for effective communication with general teams and client leadership). How much experience must I have? 7+ years of hands-on data engineering experience in production environments, with 2+ years of direct team leadership or technical management responsibility. Our Perks and Benefits: ? Learning Opportunities: - Certifications in AWS (we are AWS Partners), Databricks, and Snowflake. - Access to AI learning paths to stay up to date with the latest technologies. - Study plans, courses, and additional certifications tailored to your role.

📌 Data Engineering Manager (Argentina)
🏢 Blend360
📍 Argentina