Partner with business analysts and architects to define technical architectures for strategic projects and initiatives.
Lead the design and implementation of scalable data pipelines, data modelling and data quality frameworks.
Develop communication and education plans that help technical teams adopt technologies and processes across the data engineering ecosystem.
Contribute as an active member of product teams to support current solutions and shape future capabilities.
Mentor and guide data engineers, fostering innovation, technical excellence, and strong engineering practices within the team.
Assist in hiring & onboarding
MINIMUM QUALIFICATIONS
Education: Bachelor’s degree or equivalent practical experience in a relevant field.
Experience: 12+ years of total work experience in data architecture, data engineering, or related technology roles.
Strong experience with modern cloud platforms, preferably Google Cloud.
Hands-on experience in ETL, data warehousing, data quality, data observability, and structured and unstructured data systems.
Strong technical skills in SQL, Python, BigQuery, Composer, Dataflow, dbt, Data Modelling, Orchestration, and Prompt Engineering.
Familiarity with software engineering and delivery tools such as Git, GitHub Actions, Jira or Azure DevOps, along with Agile ways of working.
Proven ability to partner with business stakeholders, design solutions to meet business needs, and explain architecture trade-offs clearly.
Strong soft skills including communication, collaboration, adaptability, problem-solving, and ownership.
PREFERRED QUALIFICATION
Strong hands-on coding skills in Python and SQL.
Experience developing procedures and scripts for data loading, transformation, and migration.
Familiarity with Kafka and distributed computing tools.
Broader experience with cloud technologies, with Google Cloud preferred.
Strong awareness of AI, AI in data engineering.
Applicants must meet minimum age qualifications in the country in which the job is located.
