Data Engineer

What does the Data Engineer do?

The Data Engineer delivers and owns the data engineering capability for the Data and Analytics Platform.

• Building, maintaining, and supporting ingestion and transformation pipelines under the guidance of the Lead Data Engineer. Ensure that pipelines are efficient and scalable in cloud environments like Azure and Google Cloud Platform (GCP).
• Apply best practices for data engineering tasks, including data ingestion, processing, testing, monitoring, scheduling, and failure handling. Work with technologies like Azure Data Lake, Azure Synapse, Google BigQuery, SQL Server, and other relevant tools.
• Develop and implement data pipelines using tools such as Azure Data Factory (ADF) and Databricks. Follow coding standards, unit testing guidelines, and CI/CD practices to ensure high-quality, reliable data solutions.
• Deliver standard scalable components such as ADF ARM templates, Databricks components, Java, Scala and Python libraries and classes, undertake code reviews to ensure all data engineering code is of a high standard, parameterized, portable and reusable.
• Deliver and maintain code associated with integration components to third party data sources e.g. SAP, SalesForce and data applications such as Master Data Management and Data Quality solutions.
• Maintain up-to-date documentation for all data engineering processes and standards. Ensure adherence to established guidelines and practices when building and deploying data pipelines.
• Build strong collaborative relationships with Platform Engineering, Business Analytics Leads and Data Science teams.

Responsibilities

• Lead a team of 3rd parties to deliver, maintain and support the Data Engineering components and associated integrated toolsets.
• Manage the Data Engineering demand and resource allocation based on agile project demand and maintenance/support requirements.
• Contribute to the prioritization, investment and capacity planning for platform initiatives by working in tandem with peers in the Data & Analytics teams and the business teams.
• Develop strong collaborative relationships with technology teams to align technology and delivery approaches to the business needs and realization of our data strategy.
• Work with CCEP Solution Delivery to enable systems integration.
• Work with CCEP Security to ensure adherence to enterprise-wide security standards and policies.
• Work with CCEP Service Delivery to enable appropriate levels of service support.
• Research the latest analytics technologies and ways in which they can deliver value to CCEP.
• Lead engineering development of data jobs within the D&A environment.
• Provide support for local Data Engineering projects across regions.
• Learn and apply CCEP Data Pipelines Framework to effectively support BI Developers in various locations.

Qualifications:

• A Bachelor’s degree in Computer Engineering will be an advantage.
• Extensive hands-on experience in Data Engineering development (SQL, Java, Python, Scala) and in leading a team of Data Engineers for building and operating ingestion and transformation pipelines in a DevOps environment.
• Design of robust data ingestion and transformation pipelines for big scale datasets.
• Measurable experience in working with data analytics technologies such as Data Lakes, Spark, relational databases and Data Warehouses and NoSQL databases with a proven track record for the implementation of data solutions in a PaaS cloud environment.
• Good knowledge and understanding of different technologies (Azure, GCP, SAP BW) and how they co-exist to create an Enterprise Data & Analytics Platform.
• Ability to communicate clearly and concisely, including the ability to convey architectural concepts, strategy and vision to executive level.
• Experience working with internationally dispersed teams with successful outcomes.