Remote Senior Data Engineer - Ingest & Integrations

Epam Systems Inc; Buenos Aires; Híbrido; ARS 139.086.000 - 200.903.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Hybrid work

Career development

Training & certifications

Wellbeing program

Descripción de la vacante

Endava is seeking a senior data engineering leader to own the design, development, and productionization of scalable data pipelines and architectures. You will own Airflow DAGs, DBT validations, Snowflake data models, and AWS-based platforms, collaborating across product, architecture, and DevOps teams.

You will mentor engineers, review code, and drive CI/CD and Infrastructure-as-Code practices, while ensuring reliability, performance, and cost efficiency in large-scale data workloads.

Formación

• 5+ years of professional experience in data engineering or related software engineering.
• Hands-on experience building production-grade data pipelines.
• Deep knowledge of Airflow DAGs, scheduling, retries, and monitoring.
• Experience with Snowflake or equivalent cloud data warehouse platforms.
• Proven DBT experience and strong Python/SQL skills.
• Experience with AWS and CI/CD practices.
• Strong communication and documentation skills.

Responsabilidades

• Design, develop, and maintain scalable ETL/ELT pipelines for data ingestion, transformation, validation, and delivery.
• Build reusable, modular data processing solutions and contribute to technical architecture.
• Design and optimize data models, SQL queries, and data workflows.
• Develop and maintain Airflow workflows with monitoring and error handling.
• Implement data quality checks using DBT and SQL and monitor data pipelines.
• Develop data solutions using AWS and Snowflake, and manage cloud storage/compute.
• Support CI/CD pipelines and Infrastructure‑as‑Code (Terraform) for production systems.
• Provide technical leadership, code reviews, and mentorship to engineers.

Conocimientos

Python

SQL

Apache Airflow

Snowflake

DBT

AWS

CI/CD

Terraform

Herramientas

Snowflake

DBT

AWS

Terraform

Descripción del empleo

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.

Qualifications

• 5+ years of professional experience in data engineering or a related software engineering role.
• Strong hands‑on experience building and supporting production‑grade data pipelines.
• Strong knowledge of Apache Airflow, including DAG development, scheduling, dependencies, retries, and monitoring.
• Strong experience with Snowflake or equivalent cloud data warehouse technologies.
• Proven experience with DBT.
• Solid experience with AWS or another major cloud platform.
• Experience with CI/CD and Infrastructure‑as‑Code practices.
• Strong programming skills in Python and SQL.
• Demonstrated experience troubleshooting complex production issues and performing root cause analysis.
• Ability to independently own complex technical initiatives from design through implementation and production.
• Strong communication, problem‑solving, and technical documentation skills.

Preferred Qualifications

• Experience with large‑scale data processing.
• Experience with PySpark and EMR.
• Experience mentoring engineers and contributing to technical standards and architecture.

Benefits

• 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.