Build and maintain high-quality, reliable data solutions and own them with a high degree of automation in the cloud.
Own complex tasks in the backlog and deliver them routinely with no significant issues.
Support other data/ML engineers to produce clean, quality code through code reviews and pair programming.
Design, develop, and maintain scalable data/ML pipelines that adhere to ETL principles and business goals.
Drive solutions through experimentation and innovation.
Work with the data architect to build the core data model for the organization both from an operational and analytical perspective.
Support the build of analytical tools that use the data pipeline to deliver actionable insights, enabling data-driven decision-making, operational efficiency, and other key business performance metrics.
Solve problems collaboratively, communicating decisions to customers.
Approach, contribute, and help lead product planning and roadmap with an agile mentality.
Engage with product colleagues to improve value for the customer and to understand ambiguous requirements.
Promote technology, innovation, values, and ways of working within the team and wider community.
Active participation and contribution to technical forums with a focus on positive momentum.
Coach, mentor, and develop by providing the knowledge and assets to less experienced engineers.
Help lead initiatives to take M&S Data/ML Engineering to the next level by challenging the status quo.
Requirements & Skills:
Extensive proven experience in cloud-based data technologies and data warehousing design principles, preferably Azure.
Sophisticated understanding of design/building end-to-end data/ML solutions.
Solid experience with ETL tools, Databricks, and SQL.
Articulable knowledge of schema design and dimensional data modelling, automation processes, and version control tools.
Demonstrable experience in building end-to-end ML systems and ML Lifecycle (Feature engineering, monitoring, testing, deployment).
Solid experience in ML and AI concepts.
Solid experience with Python/SQL/Spark.
Proven expertise with distributed version control systems like GitHub.
Good knowledge of Continuous Integration and Continuous Delivery.
Proficiency in documenting solution design technical decisions and recommendations.
Excellent written and verbal communication skills.
