Senior Data Engineer

Why Valtech? We’re the experience innovation company - a trusted partner to the world’s most recognized brands. To our people we offer growth opportunities, a values-driven culture, international careers and the chance to shape the future of experience.

The opportunity

At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries.

We are proud of:

• The work we do and the innovation we drive
• Our values of share, care and dare
• A workplace culture that fosters creativity, diversity and autonomy
• Our borderless, global framework, which enables seamless collaboration

The role

As a Data Engineer, you are passionate about experience innovation and eager to push the boundaries of what’s possible. You bring 4+YEARS of experience, a growth mindset and a drive to make a lasting impact.

You will thrive in this role if you are:

• A curious problem solver who challenges the status quo
• A collaborator who values teamwork and knowledge-sharing
• Excited by the intersection of technology, creativity and data
• Experienced in Agile methodologies and consulting (a plus)

Role responsibilities

Data Infrastructure & Architecture

• Design and implement robust, scalable data architectures and pipelines

• Build and maintain ETL/ELT processes for batch and real-time data processing

• Develop data models and schemas optimized for analytics and reporting

• Ensure data quality, consistency, and reliability across all data systems

Platform-Agnostic Development

• Work with multiple cloud platforms (AWS, Azure, GCP) based on client requirements

• Implement data solutions using various technologies and frameworks

• Adapt quickly to new tools and platforms as project needs evolve

• Maintain expertise across different cloud ecosystems and services

Data Pipeline Development

• Create automated data ingestion pipelines from various sources (APIs, databases, files, streaming)

• Implement data transformation logic using modern data processing frameworks

• Build monitoring and alerting systems for data pipeline health

• Optimize pipeline performance and cost-efficiency

Collaboration & Integration

• Work closely with data scientists, analysts, and business stakeholders

• Collaborate with DevOps teams to implement CI/CD for data pipelines

• Partner with client teams to understand data requirements and deliver solutions

• Participate in architecture reviews and technical decision-making

Must have qualifications

Technical Skills

• Minimum 3+ years of experience in data engineering or related field

• Strong programming skills in Python and/or Scala/Java

• Experience with SQL and database technologies (PostgreSQL, MySQL, MongoDB)

• Hands-on experience with data processing frameworks:

• Apache Spark, Hadoop ecosystem

• Apache Kafka for streaming data

• Apache Airflow or similar workflow orchestration tools

• Knowledge of data warehouse concepts and technologies

• Experience with containerization (Docker, Kubernetes)

• Understanding of data modeling principles and best practices

Cloud & Platform Experience

• Experience with at least one major cloud platform (AWS, Azure, or GCP)

• Familiarity with cloud-native data services:

• Data lakes, data warehouses, and analytics services

• Serverless computing and event-driven architectures

• Identity and access management for data systems

• Knowledge of Infrastructure as Code (Terraform, CloudFormation, ARM templates)

Data & Analytics

• Understanding of data governance and security principles

• Experience with data quality frameworks and monitoring

• Knowledge of dimensional modeling and data warehouse design

• Familiarity with business intelligence and analytics tools

• Understanding of data privacy regulations (GDPR, CCPA)

Nice to have qualifications

Advanced Technical Skills

• Experience with modern data stack tools (dbt, Fivetran, Snowflake, Databricks)

• Knowledge of machine learning pipelines and MLOps practices

• Experience with event-driven architectures and microservices

• Familiarity with data mesh and data fabric concepts

• Experience with graph databases (Neo4j, Amazon Neptune)

Industry Experience

• Experience in digital agency or consulting environment

• Background in financial services, e-commerce, retail, or customer experience platforms

• Knowledge of marketing technology and customer data platforms

• Experience with real-time analytics and personalization systems

Soft Skills