Lead Data Engineer

In this role, the Lead Data Engineer for the Customer 360 Data Product will spearhead technology and data initiatives aimed at enhancing business value and outcomes within the Customer and Sales data domain. This individual will be responsible for proposing and implementing integration protocols, data acquisition and ingestion processes, business curation, and establishing a consistent Common Data Model. Additionally, they will enable teams to analyse large datasets effectively.

The Lead Data Engineer will collaborate with various business units across different regions, as well as Data and Technology teams, to foster a unified approach to the development, adoption, and governance of data products. This role focuses on enabling business use cases based on the organisation's value proposition and impact, while shaping a coherent roadmap for the ongoing evolution of the Data Product.

Responsibilities:

• Techno-Functional Expertise: Serve as a bridge between technical and functional teams, ensuring that data initiatives align with business objectives and technical requirements.
• Collaborate on Data Strategy: Work closely with Data Products and Solution teams to identify and prioritise data requirements, defining the Customer data strategy for key Use Cases.
• Hands-On Data Activities: Engage in hands-on activities related to data integration, data operations processes, and data engineering logic, contributing to the execution of prioritised Use Case Solutions in the customer data domain.
• Data Product Governance: Collaborate with business data owners and regional partners to establish and maintain data governance frameworks, ensuring alignment with organisational goals.
• Design and Build Data Capabilities: Identify and recommend methodologies and tools for building data capabilities that meet business needs, ensuring efficient scalability, flexibility, and performance.
• Data as a Product Accountability: Ensure high data quality standards, including completeness, harmonisation, standardisation, documentation, accessibility, usability, interoperability, and scalability.
• Key Design and Development Contributor: Actively participate in the design and development of the Customer Data Product, collaborating with cross-functional teams to evolve its Future State.
• Subject Matter Expert (SME): Provide expertise on Customer 360 data within the Solution teams, overseeing data requirements assessment and ensuring data availability for various Use Cases.

Requirements:

• Undergraduate degree in Technology, Computer Science, Statistics, Economics, applied data sciences or other related fields; advanced degree in related fields preferred.
• 5+ years in the IT space specialising in Data and Technology Architecture, Data Engineering and Data Operations is required.
• Ability to interpret data and make data-driven decisions, and to understand and propose data ingestion, storage, integration, and visualisation logic for Customer and Sales Data Domain and Syndicated data use cases is required.
• Experience in integration of data ingested from external partners and data providers is preferred.
• Deep knowledge of Data Governance, Master Data Management, Data Harmonisation, Data Cataloguing, Data Architecture, Data Quality principles and methodologies is required.
• Analytical and Critical thinking skills are required.
• Superb interpersonal and communication skills (oral and written), including the ability to explain digital concepts and technologies to business leaders, as well as business concepts to technologists.
• Strong business and financial competence.
• Minimum of 5 years of hands-on experience in Cloud Platforms (Azure, GCP, AWS) and cloud-based databases (Synapse, Databricks, Snowflake) and various data integration techniques (API, stream, file) using DBT, SQL/PySpark, and Python/Java is required.
• Knowledge of viz tools (Tableau, PowerBI, Excel) is preferred.
• 3+ years implementing data products through data mesh/fabric concepts is preferred.
• Experience working in Agile methodology; ability to define and implement prototypes and MVPs / RATs.
• Thrives on a diverse company culture, celebrating the uniqueness of our employees and committed to inclusion.
• Proud to be an equal opportunity employer.
• Experience in building integration pipelines (API, Database, Flatfiles) from external/internal sources to various destinations and Azure Data Factory.