Data Engineer II

About the role

You will design and maintain data pipelines and platform infrastructure to support customer-facing data movement, analytics, and machine learning. This role involves managing moderate-scope projects while working with engineering, product, and data science teams to build observable, scalable systems. You will own the reliability and performance of critical data flows that power key customer experiences and internal insights. The position requires active participation in on-call rotations to ensure system uptime and rapid response to incidents. You will evaluate and implement tradeoffs between batch and streaming patterns to align with business and technical constraints. Collaboration with cross-functional partners will define system interfaces and resolve technical issues across the data stack. You will partner with machine learning engineers to build infrastructure for feature serving, model inputs, and experimentation. This role is responsible for maintaining scalable and durable platform components that underpin Iterable's data products.

Key facts

What you'll do

• Build and maintain ingestion and activation platform components, including source connectors, transformation workflows, and API integrations.
• Improve system reliability through monitoring, alerting, retries, and durable execution across data pipelines.
• Manage Snowflake-based pipelines to ensure data freshness and scalability for analytics and customer delivery.
• Implement schema evolution and data quality checks to reduce discrepancies and enforce correctness.
• Partner with machine learning engineers to build infrastructure for feature serving, model inputs, and experimentation.
• Evaluate tradeoffs between batch and streaming patterns to optimize performance, cost, and operational simplicity.
• Collaborate with cross-functional teams to define interfaces and resolve technical issues in data workflows.
• Support the operational stability of data platforms by contributing to incident response and post-incident reviews.
• Work on data modeling efforts to support evolving business requirements and new product capabilities.
• Maintain and enhance SQL-based transformations to ensure correctness and efficiency in analytical datasets.
• Implement data validation frameworks to verify integrity across pipelines and downstream reports.
• Integrate with third-party systems and APIs to enable activation of data outside the core platform.
• Document system behavior and operational procedures to support maintainability and knowledge sharing.
• Contribute to architectural decisions that impact scalability, security, and long-term platform evolution.

Requirements

• 3+ years of professional experience in data engineering, software engineering, or platform infrastructure.
• Experience operating production ETL/ELT systems or data platforms at scale in a cloud or hybrid environment.
• Proficiency in Python and SQL, plus experience with Scala or Java for building robust data applications.
• Familiarity with modern data tools such as Snowflake, Databricks, S3, Postgres, or Redis in production settings.
• Understanding of data modeling principles, schema evolution strategies, and incremental processing patterns.
• Fluency in English for effective communication with global teams and stakeholders.
• Legal authorization to work in the EU to comply with regional employment regulations.
• Willingness to participate in on-call rotations to address service disruptions and support operational needs.
• Ability to work independently and collaboratively in a fast-paced, agile delivery environment.
• Commitment to writing clean, testable, and maintainable code that adheres to platform standards.

Nice to have

• Experience with Apache Spark for large-scale data processing and transformation workloads.
• Familiarity with feature stores and ML data workflows to support advanced analytics use cases.
• Familiarity with message streaming platforms such as Kafka or Pulsar for real-time data flows.
• Experience with orchestration tools like Airflow for managing complex pipeline dependencies.
• Experience with AWS and infrastructure-as-code tools such as Terraform for provisioning and automation.
• Background supporting enterprise data products with high reliability and strict uptime requirements.
• Experience with integration or performance testing for data-intensive systems to validate scalability.
• Understanding of security and compliance considerations for handling sensitive customer data.

Skills & tools

• Languages: Python, SQL, Scala, Java
• Platforms: Snowflake, Databricks, S3, Postgres, Redis
• Infrastructure: AWS, Kafka, Pulsar, Spark, Terraform, Docker, Kubernetes

Practical notes

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Salary: 55,000 to 68,000 EUR gross per year.

• Benefits: Competitive salary, equity, private medical insurance, life assurance, 8.55 EUR daily meal allowance, 22 days annual leave, balance days, paid sabbatical after 4 years, and a teleworking allowance.
• Recruitment safety: Iterable does not request money or fees during the hiring process and does not use free email services for official job offers. Report suspicious activity to talent-ops@iterable.com.
• Location details: This role is based in Lisbon, Portugal, with a hybrid work model.
• Engagement type: The position is offered as a full-time employment opportunity.
• Application deadline: No specific deadline is provided in the source information.
• Work authorization: Candidates must hold legal authorization to work in the European Union.
• On-call responsibilities: Participation in on-call rotations is required to support production systems.
• Compensation range is fixed within the specified minimum and maximum values.
• Professional experience must include data engineering or related software infrastructure roles.
• All listed requirements must be met without exception for consideration.
• Preferred skills do not replace mandatory qualifications but may strengthen the application.
• Iterable is committed to maintaining a professional and secure hiring process for all candidates.