Senior Performance Engineer: Scale & Optimize Web Apps

Epam Systems Inc; Buenos Aires; On-site; ARS 92,724,000 - 139,086,000; Full time

Job summary

Endava is seeking a Data Engineer to join our data team. You will design, build, and maintain scalable ETL/ELT pipelines, optimize data models, and contribute to architectural decisions across cloud data platforms.

You will work with Airflow, DBT, SQL, AWS, Snowflake, and CI/CD practices; mentor colleagues and aid production deployments while documenting runbooks and improving system reliability.

Responsibilities

• 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.
• 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.
• 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.
• 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.

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.

As a Data Engineer at Endava you will:

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.