Data Engineer II - Scale Pipelines & ML Infra (Remote)

Iterable; Lisboa; Híbrido; EUR 55 000 - 68 000; Tempo integral

Resumo da oferta

Iterable is a leading AI-powered customer engagement platform with offices in Lisbon, San Francisco, London, and beyond. We are seeking a Data Engineer II to build and operate data ingestion and activation components, enabling reliable data movement and analytics across the platform.

You will collaborate with data science, engineering, and product teams to evolve our data workflows, improve reliability, and support ML workflows while thriving in a highly remote/distributed environment.

Qualificações

• 3+ years of relevant experience in data engineering, software engineering, or adjacent platform and infrastructure roles.
• Experience building and operating production data pipelines, ETL/ELT systems, or data platforms at scale.
• Strong proficiency in Python and SQL, plus familiarity with at least one additional programming language such as Scala or Java.
• Experience with modern data tooling and cloud platforms such as Snowflake, S3, Databricks, Postgres, Redis, or similar systems.
• Familiarity with orchestration and workflow concepts, and with designing batch and/or streaming data systems.
• Understanding of data modeling, schema evolution, incremental processing, testing, and observability for reliable data products.
• Desire to work in a highly remote/distributed but collaborative environment.
• Willingness to participate in operational support or on-call as needed.
• Fluency in English (verbal and written).
• Legally authorized to work in the EU.
• Programming Languages: Python, SQL, Scala and/or Java
• Infrastructure: AWS, Kafka, Pulsar
• Other Relevant Technologies: Spark, Terraform, Docker / Kubernetes, ETL/ELT orchestration

Responsabilidades

• Build and operate components of our next-generation data ingestion and activation platform, including source connectors, staging and transformation workflows, diffing and incremental sync logic, and integrations with Iterable bulk APIs.
• Improve pipeline reliability, observability, and recovery through metrics, dashboards, alerting, retries, and durable workflow execution.
• Develop and maintain Snowflake-based data pipelines and data-sharing workflows that improve freshness, correctness, and scalability for analytics products and customer-facing data delivery.
• Contribute to schema evolution, data quality checks, and operational processes that reduce discrepancies and make data systems easier to support and extend.
• Partner with data science and machine learning engineers to build and harden the data infrastructure behind feature generation, feature serving, model inputs, and experimentation workflows.
• Make thoughtful tradeoffs across batch and streaming patterns, raw-to-curated data modeling, performance, and maintainability as systems scale.
• Collaborate with cross-functional partners across product, frontend, platform, SRE, and customer-facing teams to define interfaces, debug issues, and deliver high-quality solutions end to end.
• Recommend improvements to existing processes and understand resources available to overcome unforeseen issues.
• Learn to proactively anticipate small roadblocks to accomplishing tasks and use knowledge of business unit processes to navigate them successfully.

Conhecimentos

Python

SQL

Scala/Java

Snowflake

AWS

Kafka

Pulsar

Spark

Terraform

Docker/Kubernetes

Airflow

Databricks

Postgres

Redis

Ferramentas

Databricks

Postgres

Redis

Snowflake

Kafka

Pulsar

Spark

Terraform

Docker

Kubernetes

Airflow

AWS

Descrição da oferta de emprego

Iterable is a leading AI-powered customer engagement platform with offices in Lisbon, San Francisco, London, and beyond. We are seeking a Data Engineer II to build and operate data ingestion and activation components, enabling reliable data movement and analytics across the platform.

You will collaborate with data science, engineering, and product teams to evolve our data workflows, improve reliability, and support ML workflows while thriving in a highly remote/distributed environment.