Data Engineer

Join Us at Closer Consulting!

Mutual Respect, Empathy, Innovation and Professional Pride. Do you see yourself within these values?

Founded in 2006 under the mission "To Challenge Complexity", Closer Consulting is a Data Science company specialized in Business Intelligence, Advanced Analytics and Artificial Intelligence.

By developing projects in the most diverse industries – Banking, Telecommunications, Health, Retail, Energy, Insurance or Aviation – we analyze data, transforming it into knowledge for our clients, allowing them to adopt the best decision‑making for their respective organizations and businesses.

Tableau Data Engineer – Porto

We are now looking for a Tableau Data Engineer willing to accept new challenges in our Closer team in a hybrid project based in Porto.

Key Responsibilities:

• Design, build and maintain data infrastructure for Tableau‑based analytics
• Integrate data from multiple sources and transform it into usable models
• Develop, manage and upgrade Tableau Server architecture
• Support stakeholders in using Tableau solutions and implementing best practices
• Provide technical support to development teams and assist in non‑production configurations
• Monitor platform performance and produce internal Tableau reports
• Collaborate with business and technical teams to ensure accuracy and reliability of data insights

Technical Profile:

• 3 to 5 years of experience as a Data Engineer
• Strong proficiency in SQL and Python (mandatory)
• Hands‑on experience with Tableau Server architecture (mandatory)
• Solid understanding of ETL processes
• Experience with dashboard development and technical migrations
• Knowledge of SAS, Power
  BI, Dataiku, Apache Ni
  Fi and JIRA is a plus
• Agile methodology knowledge is a plus
• Previous experience in banking or credit risk is valued

Personal Profile:

• Detail‑oriented with strong analytical and problem‑solving skills
• Client‑focused with excellent communication abilities
• Able to translate technical topics into business‑relevant insights
• Proactive and comfortable in fast‑paced, changing environments
• Fluent in English (mandatory); French is a plus

Senior Dev
Ops Data Platform Engineer – Porto

Job Title: Senior Dev
Ops Data Platform Engineer

Location: Porto, Portugal

Work Regime: Full‑time & Hybrid (3 times on office)

Overview / Summary: We are looking for a Senior Dev
Ops Data Platform Engineer to help define and implement Dev
Ops standards, build the core of the future internal data platform, improve and refine existing infrastructure and codebases, architect infrastructure‑as‑code solutions, coordinate application deployments, lead initiatives within the Group Data area, handle incidents across environments, and advance automation efforts to enhance consistency, speed, and resilience.

Responsibilities and Tasks:

• Help define and implement Dev
  Ops standards and contribute to building the core of the future internal data platform.
• Improve and refine existing infrastructure and codebases, ensuring efficiency, stability, and up‑to‑date operations.
• Architect and implement infrastructure‑as‑code solutions using Terraform or Cloud
  Formation.
• Coordinate application deployments across all environments (Dev, QA, Preprod, Prod) within the Group Data ecosystem.
• Lead initiatives within the Group Data area, ensuring alignment with strategic objectives.
• Handle incidents in preproduction and production following established escalation paths.
• Advance automation efforts for assigned platforms and workflows to increase consistency, speed, and resilience.

Mandatory Requirements:

• Extensive hands‑on experience with AWS services (ECS, EC2, Cloud
  Front/WAF, Glue, Athena).
• Advanced experience with Terraform and Cloud
  Formation.
• Strong experience with Jenkins, Git, and Git
  Lab Pipelines for CI/CD.
• Deep understanding of ECS and Docker for containerised microservices.
• Expert knowledge of Linux/Unix systems and core networking.
• Proven experience with monitoring platforms such as Datadog and Coralogix.
• Experience using Jira or similar ticketing systems.
• Strong mastery of support principles in high‑demand application support environments.
• Practical exposure to Azure cloud components.

Stack Tech: AWS (ECS, EC2, Cloud
Front/WAF, Glue, Athena), Terraform, Cloud
Formation, Jenkins, Git, Git
Lab Pipelines, ECS, Docker, Linux/Unix, Networking, Datadog, Coralogix, Jira, Azure cloud components

Complementary Requirements:

• Background in delivering projects across the entire IT lifecycle.
• Familiarity with data‑driven technologies used in financial technology environments, with practical insight into their application.

Benefits:

• We do not sponsor work visas or work permits. All applicants must have the legal right to work in the country where the position is based.
• Only candidates who meet the required qualifications and match the profile requested by our clients will be contacted.

#Visionary
Future – Build the future, join our living ecosystem!

Work from Home Lead Data Software Engineer – Agile
Engine

Agile
Engine is a top‑ranking provider of software solutions to Fortune 500, Global 500, and Future 50 companies. Listed on Inc. 5000 among the fastest‑growing US companies, we are always open to talented software, UX, and data experts in the Americas, Europe, and Asia.

What you will do

• Collaborate closely with Data Scientists to understand their data requirements, model development needs, and performance optimization goals;
• Design, build, and maintain scalable data pipelines and infrastructure to support ML model development and deployment;
• Collect, process, and prepare large datasets for analysis, feature engineering, and model training;
• Implement data quality checks, validation, and monitoring to ensure the reliability and accuracy of data used in ML models;
• Optimize data storage, retrieval, and processing performance for ML workloads;
• Develop and maintain ETL (Extract, Transform, Load) processes and workflows;
• Manage data versioning, storage, and access control for ML datasets;
• Collaborate with Dev
  Ops and IT teams to ensure smooth deployment and scaling of ML models in production environments;
• Stay up‑to‑date with emerging technologies, tools, and best practices in data engineering and ML infrastructure.

Must haves

• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field;
• Proven experience as a Data Engineer, preferably in a role supporting Data Scientists;
• Strong proficiency in programming languages such as Python, Java, or Scala;
• Proficiency with data storage and processing technologies, including SQL databases, No
  SQL databases, and distributed computing frameworks (e. g. , Hadoop, Spark);
• Experience with data warehousing solutions and data integration tools;
• Experience with data pipeline and workflow management tools: AWS glue, Airflow, etc;
• Knowledge of ML frameworks (e. g. , Tensor
  Flow, Py
  Torch) and ML model deployment;
• Familiarity with cloud platforms (e. g. , AWS, Azure, Google Cloud) and containerization (e. g. , Docker, Kubernetes);
• Excellent problem‑solving skills and a collaborative mindset;
• Excellent oral and written communication skills with a keen sense of customer service.

Nice to haves

• Experience in ad/marketing environment
• Experience working with Data Lakes
• Experience with Scala
• Experience with Glue/EMR/Redshift/Airflow
• Experience with Terraform.

Benefits of joining us

• Professional growth – accelerate your professional journey with mentorship, Tech
  Talks, and personalized growth roadmaps.
• Competitive compensation – we match your ever‑growing skills, talent, and contributions with competitive USD‑based compensation and budgets for education, fitness, and team activities.
• Selection of exciting projects – join projects with modern solutions development and top‑tier clients that include Fortune 500 enterprises and leading product brands.
• Flextime – tailor your schedule for an optimal work‑life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.