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

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What’s in it For You?

About Us

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