[Hiring] Senior Data Engineer @Dotdigital

Role Description

We are seeking a Senior Data Engineer to help evolve and enhance our data platform and capabilities. You’ll work on building robust, scalable, and intelligent data systems that power real-time services, insights, and decisions across Dot Digital.

As a Senior Data Engineer, you will be responsible for:

• Delivering key data platform features.
• Designing and building data pipelines.
• Collaborating with product, analytics, and data science teams to unlock the value of data.
• Influencing technology choices, optimizing processes, and ensuring the consistent, reliable, and secure movement and storage of data across the organization.

Responsibilities:

• Design and build scalable, reliable, and secure data pipelines for streaming, batch, and real-time processing.
• Work in partnership with the Data Science teams to build scalable Pyspark workloads that can be leveraged to generate advanced models.
• Implement and optimize data models and storage solutions using Python and SQL with orchestration tools in a cloud environment.
• Leverage AI to automate both data processing and engineering processes.
• Advocate and uphold best practices for data governance, security, and monitoring.
• Collaborate cross-functionally with engineers, analysts, and data scientists to deliver impactful data solutions.
• Mentor and support junior engineers in data engineering principles and practices.
• Evaluate and recommend new tools and technologies to strengthen data services.

Qualifications

• Significant experience delivering Python-based projects for data engineering.
• Experience building and tuning spark pipelines that run at scale across large quantities of data.
• Strong hands-on experience with SQL and NoSQL databases (e.g. SQL Server, MongoDB, Cassandra).
• Proven experience with modern data warehousing and large-scale processing (e.g. Snowflake, DBT, BigQuery, Clickhouse).
• Proficient with data orchestration tools such as Airflow, Dagster, or Prefect.
• Experience with cloud platforms (Azure, AWS, or GCP) for data processing and storage.
• Practical experience with Kafka or equivalent event-driven architectures (e.g. AWS SQS, Azure EventHubs, AWS Kinesis).
• Good understanding of data modelling for OLAP and OLTP workloads.
• Familiar with agile methodologies and CI/CD processes in the context of data solutions.

Requirements

• Experienced as a senior team member on complex data engineering projects.
• Able to design and optimise data structures for high-volume systems.
• Experienced in assisting with data platform modernisation or migration to the cloud.
• Takes initiative to solve challenging data issues and drive projects forward.

Bonus

• Experience using ClickHouse as part of a data pipeline and analytics solution.
• Experience using Databricks or similar data platforms.

Benefits

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