Lead Data Engineer

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 prioritize 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 prioritized 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 organizational 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, harmonization, standardization, 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 specializing in data and technology architecture, data engineering, and data operations is required
• Ability to interpret data and make data-driven decisions and understand and propose data ingestion, storage, integration, and visualization logic for the 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 harmonization, data cataloging, data architecture, and 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.
• A 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, Power BI, 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 is committed to inclusion. Proud to be an equal opportunity employer.
• Experience in building integration pipelines (API, database, flat files) from external/internal sources to various destinations and Azure Data Factory.