Senior Application Production Engineer

Inetum Portugal; Lisboa; Presencial; EUR 60 000 - 85 000; Tempo integral

Resumo da oferta

Inetum Portugal is seeking a Senior Application Production Engineer (BI/Data) to ensure stability and performance of data platforms in production. You will act as a technical reference for L2/L3 support, collaborate with Data Engineering, BI, and Development teams, and drive improvements in observability and automation.

The role focuses on data operations, batch/streaming architectures, and proactive incident management. English is required; French is valued.

Qualificações

• Senior-level experience in Application Production Support / Data Operations (L2/L3).
• Strong background in data pipelines, ETL, and data platforms.
• Hands-on experience with Apache Kafka in production environments.

Responsabilidades

• Act as a technical reference for L2/L3 support of data applications and platforms.
• Ensure operation, stability, and performance of data pipelines and ETL processes.
• Support and operate batch and streaming data architectures.

Conhecimentos

L2/L3 support

Data pipelines

ETL processes

SQL

English fluency

French language (valued)

Ferramentas

Apache Kafka

Airflow

Descrição da oferta de emprego

Company Description

Inetum is a European leader in digital services. Inetum’s team of 28,000 consultants and specialists strive every day to make a digital impact for businesses, public sector entities and society. Inetum’s solutions aim at contributing to its clients’ performance and innovation as well as the common good.

Present in 19 countries with a dense network of sites, Inetum partners with major software publishers to meet the challenges of digital transformation with proximity and flexibility.

Driven by its ambition for growth and scale, Inetum generated sales of 2.5 billion euros in 2023.

Job Description

We are looking for a Senior Application Production Engineer (BI/Data) to ensure the stability, performance, and continuous improvement of data platforms in production, acting as a technical reference in complex batch and streaming environments.

This role has a strong focus on L2/L3 application support, data operations, and close collaboration with Data Engineering, BI, and Development teams.

Responsibilities

• Act as a technical reference for L2/L3 support of data applications and platforms
• Ensure the operation, stability, and performance of data pipelines and ETL processes
• Support and operate batch and streaming data architectures
• Operate, monitor, and troubleshoot environments based on Apache Kafka
• Perform proactive monitoring, incident detection, and root cause analysis
• Lead advanced troubleshooting of data, pipeline, and distributed system issues
• Collaborate with development teams to resolve production issues and improve system design
• Support release, deployment, and change management processes
• Propose and implement improvements in observability, resilience, and automation
• Maintain clear technical documentation and operational best practices
• Provide guidance and technical support to more junior profiles when needed

Qualifications

• Senior-level experience in Application Production Support / Data Operations (L2/L3)
• Strong background in data pipelines, ETL, and data platforms
• Hands-on experience with Apache Kafka in production environments
• Solid knowledge of batch and streaming architectures
• Experience with monitoring, alerting, and logging tools
• Proven ability to analyze and resolve complex production incidents
• Experience working in critical production environments with strict SLAs
• Strong SQL skills and experience with relational and/or analytical databases
• Good understanding of distributed systems and service dependencies
• Fluent in English
• Fluent in French (is valued)

Nice to Have

• Experience with cloud environments (AWS, Azure, or GCP)
• Knowledge of orchestration tools (e.g. Airflow)
• Experience with automation, scripting, or Infrastructure as Code
• Background in BI, Data Engineering, or Analytics Platforms
• Experience in large-scale enterprise environments