Senior Data Engineer

planet; Galway; On-site; EUR 90,000 - 150,000; Full time

Job summary

Planet seeks a Senior Data Engineer to design, build, and evolve a modern data platform focusing on Snowflake, Fivetran, and dbt. You will architect scalable data pipelines, data models, and trusted data products powering analytics, AI, and operational use cases across the organisation.

You will collaborate with Data Engineers, Data Analysts, AI Engineers, and stakeholders to ensure data accuracy, security, and availability, while driving governance, standards, and scalable patterns for future

Qualifications

• Strong experience with modern data platforms (Snowflake, Databricks, Redshift, BigQuery).
• Extensive experience building and operating ELT/ETL pipelines in production.
• Advanced SQL for large datasets.
• Hands-on data ingestion with Fivetran and API integrations.
• dbt for transformation, testing, and dimensional modelling.
• Understanding of dimensional modelling concepts and semantic layers.
• Experience in data quality, observability, and lineage solutions.
• Experience with batch, event-driven, and near real-time architectures.

Responsibilities

• Design, develop, and optimise scalable data pipelines using ELT tools, APIs, and databases.
• Lead integration of new data sources into Snowflake with reusable ingestion patterns.
• Design and implement ETL/ELT processes for large-scale analytics and AI workloads.
• Define ingestion patterns for incremental, CDC, full refresh, and near real-time data.
• Operate reverse ETL pipelines delivering data to operational systems and APIs.
• Improve platform reliability, performance, observability, and cost.
• Maintain dbt-based data transformation frameworks and models.
• Develop and maintain complex dimensional models and semantic structures.
• Define standards, naming conventions, and governance across the platform.
• Implement automated testing, data quality, and lineage tracking.

Skills

Snowflake

SQL

Fivetran

dbt

ETL pipelines

Cloud platforms

Tools

Databricks

CI/CD

Job description

About Planet

Planet is a global provider of integrated technology and payments solutions for retail and hospitality customers.

We create great experiences for the millions of people who use our payments, software, and tax-free solutions every minute of every day.

Planet empowers its customers to deliver great customer experiences by combining payments and software in ways that drive greater loyalty, increase revenue and save time.

Founded over 35 years ago and with our headquarters in London, today we have more than 2,500 employees located across six continents serving our customers in more than 120 markets.

Role Overview:

This is a long-term fixed-term contract designed to support Planet's AI-first engineering scale-up project.

As a Senior Data Engineer, you will play a key role in designing, building, and evolving Planet's modern data platform, with a focus on Fivetran, Snowflake, and dbt. You will be responsible for architecting scalable data pipelines, data models, and trusted data products that power analytics, AI, agentic, predictive, and operational use cases across the organisation.

Working closely with Data Engineers, Data Analysts, AI Engineers, and business stakeholders, you will ensure that data is accurate, reliable, secure, and readily available. You will also drive architectural decisions, define engineering standards, mentor other engineers, and contribute to the long-term scalability, reliability, and governance of the data platform.

What You Will Do:

• Design, develop, and optimise scalable data pipelines using ELT tools, APIs, databases, and event-based architectures.
• Lead the integration of new data sources into Snowflake, defining reusable ingestion patterns and engineering standards.
• Design and implement ETL/ELT processes that support large-scale analytics, AI, and operational workloads.
• Define and implement ingestion patterns for incremental, CDC, full refresh, and near real-time data processing scenarios.
• Design and operate reverse ETL pipelines that deliver trusted data products to operational systems, applications, and APIs.
• Drive continuous improvement of platform reliability, performance, observability, and cost optimisation.
• Design and maintain scalable data transformation frameworks using dbt.
• Develop and maintain complex dimensional models, including fact, dimension, snapshot, and semantic data structures.
• Define modelling standards, naming conventions, and best practices to ensure consistency across the data platform.
• Implement automated testing, data quality frameworks, lineage tracking, and monitoring solutions.
• Design and maintain trusted datasets and data products for analytics, AI, self-service, and operational use cases.
• Collaborate with stakeholders to understand business requirements and translate them into scalable technical solutions.
• Lead troubleshooting and resolution of complex data platform, pipeline, and performance issues.
• Drive data governance initiatives, including data ownership, metadata management, lineage, schema evolution, and data contracts.
• Maintain and promote engineering documentation, technical standards, architectural patterns, and operational runbooks.
• Mentor Associate and Mid-Level Data Engineers through code reviews, technical coaching, and knowledge sharing.
• Evaluate emerging technologies and recommend improvements to enhance platform capabilities and support future growth.
• Ensure all data solutions comply with security, privacy, governance, and regulatory requirements.

Who You Are:

• Strong experience with modern data platforms such as Snowflake, Databricks, Redshift, BigQuery, or similar technologies.
• Extensive experience building and operating ELT/ETL pipelines in production environments.
• Advanced SQL skills for querying, transforming, optimising, and analysing large datasets.
• Strong hands-on experience with data ingestion tools such as Fivetran and API-based integration patterns.
• Strong experience with dbt for data transformation, testing, documentation, and dimensional modelling.
• Deep understanding of dimensional modelling concepts, including facts, dimensions, metrics, snapshots, and semantic layers.
• Experience implementing data quality, observability, monitoring, and lineage solutions.
• Experience designing batch, event-driven, and near real-time data architectures.
• Strong understanding of reverse ETL patterns and operational data delivery.
• Experience with software engineering practices including Git, CI/CD pipelines, automated testing, and Infrastructure as Code.
• Strong knowledge of cloud platforms such as Azure, AWS, or GCP and their data services.
• Strong understanding of data governance, metadata management, security, privacy, and compliance best practices.
• Excellent problem-solving and analytical thinking skills.
• Ability to evaluate technical trade-offs and make architectural decisions balancing scalability, maintainability, performance, and cost.
• Strong communication skills and ability to engage effectively with technical and no