SENIOR, DATA ENGINEER

Demonstrates up-to-date expertise and applies this to the development, execution, and improvement of action plans by providing expert advice and guidance to others in the application of information and best practices; supporting and aligning efforts to meet customer and business needs; and building commitment for perspectives and rationales.
Provides and supports the implementation of business solutions by building relationships and partnerships with key stakeholders; identifying business needs; determining and carrying out necessary processes and practices; monitoring progress and results; recognizing and capitalizing on improvement opportunities; and adapting to competing demands, organizational changes, and new responsibilities. Models compliance with company policies and procedures and supports company mission, values, and standards of ethics and integrity by incorporating these into the development and implementation of business plans; using the Open Door Policy; and demonstrating and assisting others with how to apply these in executing business processes and practices. What youll do...

• Design and lead the development of enterprise-scale data platforms that support advanced analytics, real-time decisioning, and machine learning use cases across the organization.
• Drive architectural decisions and set engineering standards for data ingestion, transformation, storage, and access ensuring scalability, reliability, and performance.
• Collaborate with cross-functional teams including product managers, data scientists, analysts, and software engineers to translate business needs into robust data solutions.
• Champion data quality, governance, and observability, implementing frameworks and tools to ensure trusted, compliant, and well-documented data assets.
• Mentor and influence engineering teams, fostering a culture of innovation, technical excellence, and continuous improvement across the data engineering function.

• High to Extensive experience (6+ years) in data engineering, with a proven track record of building and scaling complex data systems in cloud-native environments (e.g., GCP, AWS, Azure).
• Deep expertise in modern data technologies such as Spark, Kafka, Airflow, BigQuery, Snowflake, Delta Lake, and orchestration frameworks.
• Strong programming and data modeling skills, particularly in Python, SQL, and distributed computing paradigms.
• Experience leading large-scale data initiatives, including data platform modernization, real-time streaming, and data mesh or lakehouse architectures.
• Excellent communication and leadership abilities, with the capability to influence technical direction, align stakeholders, and drive strategic outcomes.