Principal Data Engineer, Dotdigital

• Technical Expertise:
• 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
• Capable in the wider software development lifecycle in terms of agile ways of working and continuous integration/deployment of data solutions
• 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

Desirable

• We are on the lookout for a Principal Data Engineer to help define and lead the next generation of our data platform and data capabilities
• You’ll play a key role in building scalable, resilient and intelligent data systems that power real time services, insights, products and decisions across Dotdigital
• As a Principal Data Engineer, you will be instrumental in driving the architecture, development and delivery of our data platform
• You will lead key initiatives, provide technical direction and collaborate with product, analytics and data science teams to ensure data value is realised across the entire ecosystem
• Working across the entire data lifecycle, you will help shape how data is collected, processed and consumed across Dotdigital
• 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

• 15 min Screening Call with Talent Team
• Stage 1: Role deep dive with hiring manager(s)
• Stage 2: Technical interview with data team