About this role
<div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="font-size:16.0px;word-wrap:break-word"><H2 style="font-size:1.0em;margin:0.0px">Job Purpose and Impact</H2> </div><div><p>The Principal, Data Engineering job provides thought leadership in the execution of strategic plans related to design, development and maintenance of robust data systems. As a recognized subject matter expert in the field, this job leads the development of efficient processing and availability of data for analysis and reporting.</p></div></div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="font-size:16.0px;word-wrap:break-word"><H2 style="font-size:1.0em;margin:0.0px">Key Accountabilities</H2> </div><div><ul type="disc"> <li>DATA PIPELINES: Provides thought leadership on the design and development of data pipelines that facilitate the movement of data from various sources to internal databases.</li> <li>DATA INFRASTRUCTURE: Influences the construction and optimization of data infrastructure, providing appropriate data formats to ensure data readiness for analysis.</li> <li>DATA FORMATS: Examines and sees improvement opportunities for appropriate data formats to optimize data usability and accessibility across the organization.</li> <li>STAKEHOLDER MANAGEMENT: Cultivates positive relationships and partners to understand data needs and encourage alignment with organizational objectives.</li> <li>DATA SYSTEMS: Develops and guides the implementation of data products and solutions using advanced engineering and cloud-based technologies, ensuring they are designed and built to be scalable, sustainable, and robust.</li> <li>SOLUTIONS DEVELOPMENT: Leads efforts to improve the development of technical products and solutions driving big data and cloud-based technologies, ensuring they are designed and built to be scalable, sustainable, and robust.</li> <li>DATA FRAMEWORKS: Drives development standards and brings forward prototypes to test new data framework concepts and architecture patterns supporting efficient data processing and analysis and promoting standard methodologies in data management.</li> <li>AUTOMATED REPORTING SYSTEMS: Builds automated reporting systems that provide timely insights and facilitate data driven decision making.</li> <li>DATA MODELING: Provides thought leadership on data modeling and preparation of data in databases for use in various analytics tools and to develop data pipelines to move and improve data assets. </li> </ul></div></div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="font-size:16.0px;word-wrap:break-word"><H2 style="font-size:1.0em;margin:0.0px">Qualifications</H2> </div><div><ul> <li>Minimum requirement of 6 years of relevant work experience. Typically reflects 10 years or more of relevant experience.</li> </ul> <p>PREFERRED QUALIFICATIONS</p> <ul type="disc"> <li>ARCHITECTURAL LEADERSHIP: Defines long-term technical direction, establishes best practices, and ensures solutions are scalable, maintainable, and aligned with enterprise strategy.</li> <li>OPERATIONAL EXCELLENCE MINDSET: Champions reliability, observability, and performance, ensuring data systems meet high standards for availability and quality.</li> <li>STRATEGIC DECISION MAKING<strong>:</strong> Evaluates competing priorities such as speed, cost, risk, and flexibility to make sound technical and architectural decisions.</li> <li>CLOUD DATA PLATFORMS<strong>:</strong> deep expertise implementing cloud-based data warehouses, data lakes, and open table formats in large-scale production environments. Has hands-on experience with technologies such as Snowflake, AWS, and open lakehouse ecosystems.</li> <li>DATA INGESTION: Demonstrated proficiency in data collection, ingestion tools (Kafka, AWS Glue), and storage formats (Iceberg, Parquet)</li> <li>DATA STREAMING: Experience developing data pipelines with streaming architectures and tools (Kafka, Flink).</li> <li>DATA TRANSFORMATION: Strong background with using Spark for data transformation, including streaming, performance tuning, and debugging with Spark UI.</li> <li>DEVOPS: extensive experience in DevOps practices, including code management, CI/CD, and deployment strategies.<br><br></li> </ul> <p><span style="color:white">#HiPo</span></p></div></div></div>