Who We Are:
Brooks is a team of passionate people united by a desire to do meaningful work, lead healthy lives and make a difference. We share a focused mission: to inspire everyone to run and be active. That’s it. No distractions—it’s all about the run. Through science, creativity, service, authenticity and connection, we obsess over delivering the best running gear on the planet. We do it our way, with our unique spirit, with a goal of being more relevant to runners than any other brand, day after day and mile after mile. We are determined to innovate, challenging ourselves to lead thought at every turn. Inside these walls and on the roads, tracks and trails, we live and breathe Run Happy, celebrating the positive impact running has on our lives and others. We inject it into all we do because it makes everything better, smarter, more fun and more memorable. Our company culture defines us, bonds us together and creates the conditions for success. It is lived daily as a behavioral expression of our collective set of brand values: Connect with People, Innovate for our Customer, Compete as a Team, Build Trust, Have Fun & Bring Passion, and Be Active. If you’re on our team, it means you’re part of creating something extraordinary. You’re part of Brooks.
Brooks is rapidly modernizing and expanding its data and analytics platform leveraging cloud capabilities. As the Cloud Data Engineer, you will have the opportunity to put your stamp on how things are done! We are creating a cloud-first platform leveraging AWS and Snowflake as core technologies supported by relational database ingestion patterns, API ingestion patterns, and flat file ingestion patterns with planned growth in the IoT and machine learning space. The successful candidate will be responsible for evolving our modern data platform through planning, building and supporting enterprise grade production data pipelines across disparate sources. You will need to lead by example, partner with peers, and push the bounds of what is possible. We are excited to find someone who will be a critical part of our team and elevate the enterprise’s use of data.
⏵ Build complex and scalable production level data pipelines; from source to data products ready for end-user consumption (e.g. multi-dimensional model).
⏵ Support all production data pipelines; as required, provide on-call support and after-hours maintenance and upgrades.
⏵ Collaborate with business users to understand the need / problem, break down requirements, and maintain communication through delivery.
⏵ Collaborate with Data Modeler, BI developers, and platform owners to define the scope, design, and implement the correct solution.
⏵ Produce detailed and high-quality documentation detailing design and behaviors of data pipelines.
⏵ Work with peers in the Data & Analytics, Enterprise Applications, Engineering, Operations, and Security teams to ensure integration points are effectively defined, developed, and supported.
⏵ Provide guidance and mentorship to junior Data Analysts with technical guidance and troubleshooting assistance, regarding self-service data pipelines / data preparation, etc.
⏵ Follow established code management and documentation practices.
⏵ Adhere to IT department ITIL change management processes to ensure changes are authorized, documented and tested before implementation in the production environment.
⏵ Maintain awareness of advancements, innovations and changes in technologies relating to data engineering, cloud data platforms, data models, enterprise information management, business intelligence and data science and provide recommendations from a data engineering perspective.
⏵ Participate in architectural evolution of Brooks’ data engineering patterns, frameworks, systems, and platforms including defining best practices, standards, principles, and policies.
⏵ Instill comprehension of technical concepts for non-technical audiences through presentations (executive leadership and large groups), email, and meetings.
⏵ Bring a positive energy every day and work within a team to deliver the best possible solutions.
⏵ Learn the business and the data that supports the business; don’t just implement technology.
⏵ Other responsibilities as required.
⏵ Degree in Computer Engineering/Science, Information Systems, or related field
⏵ 4+ years professional experience in data warehouse ETL / data engineering development
⏵ 2+ years current professional experience in cloud-based ELT data engineering development
⏵ Current expert knowledge of languages: Python, Java, or Scala (Python required)
⏵ Current experience with developing on MPP database technologies (Snowflake required)
⏵ Current experience with developing on a Public Cloud Environment (AWS preferred)
⏵ Proficient with data preparation tools (Alteryx preferred)
⏵ Expert knowledge of SQL (T-SQL, MSSQL, TSQL and NoSQL) including programmability features and techniques, as well as best practices for performance and readability
⏵ Experience in development, design, and application of data modeling (on star-schema model), data mining and data architecture concepts and techniques
⏵ Experience working in an Agile team and delivery capability
⏵ Strong written skills and verbal/presentation skills
⏵ Familiarity with Data Visualization platforms (e.g. Tableau and Power BI)
⏵ Familiarity with common security measures for analytical systems
⏵ Experience with source control tools
⏵ Embraces and lives Brooks values!
At Brooks, we celebrate diversity & equity. We are committed to creating an inclusive environment, and encourage people of all backgrounds, perspectives, experiences, and skills to apply. Brooks is proud to be an equal employment opportunity employer. All employment decisions are made without regard to race, religion, color, national origin, gender, gender identity, the presence of a sensory, physical or mental disability, medical condition, military status, marital status, pregnancy or child birth, sexual orientation, age, genetic information, status as a victim of domestic violence, sexual assault or stalking, political ideology, or any other non-merit based factors.
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