Senior Data Engineer - Ingestion & Cloud (Remote Latam)

YO AI Labs; Rosario; Hybrid; ARS 139,086,000 - 200,903,000; Full time

Benefits offered by this job

Hybrid work

Flexible hours

Learning & development

Wellbeing program

Global tech communities

Job summary

Endava is seeking a senior Data Engineering & Architecture leader to shape scalable data pipelines, orchestrations, and quality checks. You will design ETL/ELT architectures, guide Airflow workflows, and collaborate with cross‑functional teams to deliver reliable data services.

You will mentor engineers, implement IaC with Terraform, deploy on AWS and Snowflake, and drive production readiness through monitoring, tests, and documentation.

Qualifications

• Design scalable ETL/ELT pipelines and data architectures.
• Lead data engineering initiatives from design to production, mentoring engineers.
• Develop automated data quality checks and observability.

Responsibilities

• Design, build, and maintain scalable data pipelines and architectures.
• Develop reusable, modular data processing solutions.
• Lead Airflow workflows and data quality checks using DBT and SQL.

Skills

Data Architecture

Leadership

Data Modeling

Python

SQL

Cloud Data Platforms

Data Pipelines

Technical Strategy

Tools

Airflow

DBT

Snowflake

SQL

AWS

Terraform

Job description

Our data team has expertise across engineering, analysis, architecture, modeling, machine learning, artificial intelligence, and data science. This discipline is responsible for transforming raw data into actionable insights, building robust data infrastructures, and enabling data-driven decision-making and innovation through advanced analytics and predictive modeling.

Data Engineering & Architecture

• Design, develop, and maintain scalable ETL/ELT pipelines for data ingestion, transformation, validation, and delivery.
• Develop reusable, modular, and configuration-driven data processing solutions.
• Contribute to technical architecture and evaluate solutions based on scalability, performance, reliability, and maintainability.
• Design and optimize data models, SQL queries, stored procedures, and data processing workflows.

Workflow Orchestration & Data Quality

• Design and maintain Apache Airflow workflows, including scheduling, dependencies, retries, monitoring, and error handling.
• Develop automated data validation and quality checks using DBT and SQL.
• Implement appropriate monitoring, alerting, and observability for critical data pipelines.
• Troubleshoot and resolve complex data processing and quality issues.
• Develop data solutions using AWS and cloud-based data warehouse technologies such as Snowflake.
• Work with cloud services for data storage, processing, compute, messaging, and serverless workloads.
• Support data platforms across development, QA, staging, and production environments.
• Optimize data workloads for performance, scalability, reliability, and cost.

CI/CD & Production Support

• Develop and maintain CI/CD pipelines for data engineering applications and infrastructure.
• Apply Infrastructure-as-Code practices using Terraform or equivalent technologies.
• Support production deployments, incident resolution, root cause analysis, and continuous improvement.
• Maintain technical documentation, operational runbooks, and troubleshooting guides.

Technical Leadership

• Take ownership of complex engineering initiatives from design through production.
• Conduct code reviews and promote engineering best practices.
• Mentor junior and mid-level engineers and provide technical guidance.
• Collaborate with architecture, DevOps, product, and other technology teams.

Additional Information

• Finance: Competitive salary package, value-based recognition awards, referral bonus;
• Career Development: Career coaching, global career opportunities, non-linear career paths, internal development programmes for management and technical leadership;
• Learning Opportunities: Complex projects, rotations, internal tech communities, training, certifications, coaching, online learning platforms subscriptions, pass-it-on sessions, workshops, conferences;
• Work-Life Balance: Hybrid work and flexible working hours, employee assistance programme;
• Health: Global internal wellbeing programme, access to wellbeing apps;
• Community: Global internal tech communities, hobby clubs and interest groups, inclusion and diversity programmes, events and celebrations.

At Endava, we’re committed to creating an open, inclusive, and respectful environment where everyone feels safe, valued, and empowered to be their best. We welcome applications from people of all backgrounds, experiences, and perspectives—because we know that inclusive teams help us deliver smarter, more innovative solutions for our customers. Hiring decisions are based on merit, skills, qualifications, and potential. If you need adjustments or support during the recruitment process, please let us know.