ETL Developer

Role Overview

We are looking for an ETL Developer to design, build, maintain, and support robust data pipelines across operational systems, cloud data warehouses, relational databases, and BI/reporting environments. This role focuses heavily on ETL/ELT development, complex data transformation, pipeline reliability, performance tuning, and data quality metrics. The ideal candidate possesses advanced SQL mastery, hands-on experience with modern cloud data tools, and the ability to collaborate effectively with analysts, data engineering units, and business intelligence teams.

Key Information:

• Location: Argentina (Remote or Hybrid).
• Schedule: Full-time (EST time zone overlap preferred).
• Core Tech Stack Focus: Matillion, Snowflake, SQL Server.

Core Responsibilities

1. ETL/ELT Development & Data Pipeline Engineering

• Pipeline Management: Develop, maintain, and support secure ETL/ELT pipelines that ingest, move, and transform data from multiple heterogeneous source systems into Snowflake and enterprise reporting layers.
• Workflow Automation: Build, schedule, and optimize automated data workflows and jobs using Matillion, SQL Server, and Snowflake.
• Layer Architecture: Design and implement data transformation logic across storage tiers, including Staging areas, Operational Data Stores (ODS), curated data layers, and downstream reporting datasets.

2. Advanced Data Querying, Mapping & Optimization

• SQL Programming: Write, tune, and troubleshoot highly complex SQL queries across both cloud data warehouses and on-premise infrastructure.
• Data Integration Strategy: Participate in Source-to-Target Mapping (STTM), schema design, dependency mapping, and metadata alignment activities.
• Performance Engineering: Execute database indexing strategy, query profiling, pipeline performance tuning, and architecture optimization to ensure rapid data processing.

3. Data Quality, Governance & Reliability Controls

• Reconciliation Controls: Implement strict data validation checks, data reconciliation workflows, and quality enforcement rules across the entire ingest cycle.
• Fault-Tolerant Architecture: Build robust error-handling mechanisms, automated job retry logic, system dependency management, alert triggers, and pipeline health notifications.
• Root-Cause Analysis: Provide production support, monitor operational schedules, troubleshoot data drops, and perform root-cause analysis on critical batch windows.

4. Stakeholder Alignment & Documentation

• Requirements Gathering: Partner with business analysts, BI developers, app teams, and data owners to extract technical data specifications.
• Technical Writing: Author and update technical documentation, system architecture flowcharts, data lineage logs, and support runbooks.

Required Qualifications (Hard Skills)

• Education: Bachelor's degree in Computer Science, Information Systems, Software Engineering, or a strictly related field.
• Professional Journey: Verified hands-on experience in ETL/ELT development, data warehousing, or data engineering roles.
• Tooling Mastery: Demonstrated expert-level experience using Matillion and Snowflake for corporate scale data ingestion.
• Database Frameworks: Strong background working with SQL Server and cloud-native databases.
• Advanced Querying: Mastery of Advanced SQL techniques (Window functions, CTEs, query optimization, store procedures, execution plans).
• Mapping Practices: Proven experience drafting detailed Source-to-Target mappings and data transformation rules.
• Quality Assurance: Background managing automated data quality validation and data reconciliation controls.

Preferred Qualifications (Pluses)

• Experience supporting massive enterprise data warehouses, enterprise analytical hubs, or big data platforms.
• Exposure to modern Business Intelligence and reporting tools (PowerBI, Tableau, Looker) and downstream data consumption frameworks.
• Familiarity with formal data governance, master data management, metadata management, and enterprise data lineage mapping.
• Practical experience working inside Agile, Scrum, or modern iterative product delivery setups.

Key Skills & Tech Stack Summary

• Core Domain: ETL/ELT Development, Cloud Data Warehousing, Data Pipeline Engineering.
• Data Ecosystem: Matillion, Snowflake, SQL Server, Advanced SQL.
• Data Logistics: Source-to-Target Mapping (STTM), Data Transformation Logic, Staging/ODS Management.
• Governance & Security: Data Quality Validation, Data Reconciliation, Lineage, Error Handling and Alerting.
• Optimization: Performance Tuning, Query Optimization, Root Cause Analysis, Pipeline Monitoring & Orchestration.