Business Technology Analyst

Summary of the role: Are you excited by the prospect of transforming data, building sophisticated data models, and shaping the way businesses make decisions? The Go-To-Markets Data Analytics team is looking for a skilled Data Engineer who is motivated to deliver top notch data transformation and analytics engineering solutions to support business intelligence, data science, and self-service data solutions. About the role: SQL Proficiency a must 6 years' experience in data engineering with a strong focus on data transformation and analytics engineering Strong experience with dbt (data build tool) highly preferred Experience with data pipeline and transformation tools such as dbt, Glue, FiveTran, Alteryx or similar solutions Hands-on experience with CI/CD pipelines (GitHub Actions, Azure DevOps, GitLab, etc.) and strong familiarity with version control best practices, code reviews, and documentation standards. Familiarity with Agile development practices, including sprint planning, backlog grooming, iterative delivery, and cross-functional collaboration Experience with data orchestration tools like Airflow or Dagster (DPOT) Experience using cloud-based data warehouse solutions such as Snowflake, Redshift, Azure Preferred experience using Amazon Web Services (S3, Glue, Athena, QuickSight) Strong data modelling expertise with various schemas like snowflake and star Proven track record designing and implementing data transformation logic and workflows Experience building complex data models that support analytics and reporting needs Knowledge of database design and query optimization Experience with a scripting language like Python Works well within a team and collaborates with colleagues across domains and geographies Excellent oral, written, and visual communication skills Has a demonstrable ability to assimilate new information thoroughly and quickly Strong logical and scientific approach to problem-solving Can articulate complex results in a simple and concise manner to all levels within the organization About you: Build and maintain sophisticated data models using tools like dbt to ensure data quality, consistency, and accessibility  Hands-on experience with CI/CD pipelines (GitHub Actions, Azure DevOps, GitLab, etc.) and strong familiarity with version control best practices, code reviews, and documentation standards. Experience designing scalable and maintainable data architectures, aligned with engineering standards and long-term platform growth. Leverage orchestration tools (Airflow, Dagster) to schedule and monitor data transformation workflows Ability to mentor junior engineers and share industry best practices in data engineering, data modeling, and pipeline development Work closely with data scientists and data visualization teams to understand data requirements to ensure the availability of high-quality, well-transformed data for analytics, modelling, and reporting Strong troubleshooting and optimization skills, with experience improving pipeline performance, reliability, and cloud cost efficiency. Contribute to the strategy and architecture of data management systems and solutions Proactively troubleshoot and resolve data transformation, data quality, and performance bottlenecks in a timely manner Be open to learning and working on emerging technologies in data engineering, analytics engineering, data science and cloud computing space Have the curiosity to interrogate data, conduct independent research, utilize various techniques, and tackle ambiguous problems Self‑driven and proactive, able to work with minimal supervision, take ownership of deliverables, and step up to additional responsibilities as business needs evolve #LI-NR1 What’s in it For You? Hybrid Work Model: We’ve adopted a flexible hybrid working environment (2-3 days a week in the office depending on the role) for our office-based roles while delivering a seamless experience that is digitally and physically connected ... (truncated, view full listing at source)