Principal Data Engineer

October 24

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Dotdigital

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SaaS • Marketing

Dotdigital is a marketing automation platform, established over 20 years ago, that helps brands improve their marketing engagement using innovative tools to achieve seamless and relevant customer connections. With over 400 employees worldwide, Dotdigital serves mid-market and enterprise companies across various industries, emphasizing responsible marketing and sustainability. The company is recognized as the world's first carbon-neutral marketing automation platform with certifications in ISO14001, ISO 27701, and ISO27001. Dotdigital is committed to diversity and inclusion, and actively supports initiatives for green practices, employee wellbeing, and women empowerment in the tech industry.

201 - 500 employees

Founded 1999

☁️ SaaS

📋 Description

• Lead the design and implementation of scalable, secure and resilient data systems across streaming, batch and real-time use cases. • Architect data pipelines, model and storage solutions that power analytical and product use cases; using primarily Python and SQL via orchestration tooling that run workloads in the cloud. • Leverage AI to automate both data processing and engineering processes. • Assure and drive best practices relating to data infrastructure, governance, security and observability. • Work with technologists across multiple teams to deliver coherent features and data outcomes. • Support the data team to help adopt data engineering principles. • Identify, validate and promote new tools and technologies that improve the performance and stability of data services.

🎯 Requirements

• Extensive experience delivering python-based projects in the data engineering space. • Extensive experience working with SQL and NoSQL database technologies (e.g. SQL Server, MongoDB & Cassandra). • Proven experience with modern data warehousing and large-scale data processing tools (e.g. Snowflake, DBT, BiqQuery, Clickhouse). • Hands on experience with data orchestration tools like Airflow, Dagster or Prefect. • Experience using cloud environments (e.g. Azure, AWS, GCP) to process, store and surface large scale data. • Experience using Kafka or similar event-based architectures e.g. (Pub/Sub via AWS SQS, Azure EventHubs, AWS Kinesis). • Strong grasp of data architecture and data modelling principles for both OLAP and OLTP workloads. • Engineering Leadership Experience as a lead or Principal Engineer on large-scale data initiative or product builds. • Demonstrated ability to architect data systems and data structures for high volume, high throughput systems. • Proven experience leading data platform modernisation or cloud migration projects. • Comfortable taking ownership of difficult data problems and driving them to resolution.

🏖️ Benefits

• Parental leave • Medical benefits • Paid sick leave • Dotdigital day • Share reward • Wellbeing reward • Wellbeing Days • Loyalty reward • DEI commitment