As the Lead Data engineer , you have in depth experience and a passion for working with data at scale at a large company. You are a pro at finding solutions and tools to help the organization optimize their business performance by managing, sorting and filtering volumes of data as well as extracting meaningful value from these large volumes of data.
You will design and build robust data pipelines using scalable tools and techniques (to produce high quality data structures and Implement quicker data processing methods and integrate complex business logic compatible with daily or real-time/streaming frameworks.
You are self-directed, operationally minded, and motivated, with strong data, project management, and influencing skills and thrive thrives in a team setting where you can use your creative and analytical prowess to obliterate problems. You’re passionate about digital technology, and you take pride in making a tangible difference.
Job Duties/ Accountabilities :
Critical Qualifications/ Competencies:
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
- Work with business partners, other product managers, developers and engineering to gather functional and technical requirements around Data infrastructure and architecture
- Be the guiding voice of the Bell Media data analytics infrastructure roadmap
- Build, maintain and evolve the data analytics stack
- Oversee and manage AWS infrastructure and cost
- Create the foundational layer of Bell Media’s modern data analytics stack, migrating brands such as Crave, TSN and CTV from on-perm to cloud based SaaS and serverless technologies
- Work with POs, developers and other internal stakeholders to keep them abreast of changes, features and new functionality impacting their daily work
- Manage vendor relationships and support tickets
- Integrate internal and external data sources via APIs or custom pipelines
- Own all BI and product tool integrations e.g. Looker, Google Analytics, Braze, etc
- Manage and mentor analytics engineer
- 5+ years of hands-on years as a Data Engineering or an Analytics Engineer Experience with cloud based applications.
- Knowledge in AWS (preferred), Azure or GCP -
- Experience in AWS services such as Redshift, Lambda, Glue, EMR, EC2, EKS and Step Functions
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Previously built or maintained modern data analytics stack infrastructure
- Experience in orchestration tools like Airflow, Dagster, Perfect or dbt cloud
- Experience in dbt (preferred) and data modeling in general
- Working knowledge of BI tools such as Looker, Tableau, Mode or Metabase
- Experience in DataOps or Software CI/CD practices
- High-energy self-starter with experience and passion for data and big data scale processing. You enjoy working in fast-paced environments and love making an impact.
- Exceptional communicator with the ability to translate technical concepts into easy-to-understand language for our stakeholders
- AWS certificates or experience in cloud based ML solutions