As a Data Engineer, you will be responsible for designing, developing, maintaining, and optimising a data pipeline infrastructure using a proprietary data platform , which is based on Databricks. You will collaborate with cross-functional teams to design and implement scalable data solutions, ensuring efficient data ingestion, transformation, storage, and analysis.
Team Management: Accountable for leading a compact team of data engineers, ensuring strong technical guidance, efficient delivery, clear goal-setting, and ongoing mentoring. Also contributes to performance reviews and actively supports the recruitment process.
Data Product Design & Development: Oversees the end-to-end delivery of scalable data products, infrastructure, and pipelines, primarily using Databricks. This includes implementing robust ingestion, processing, and storage solutions, as well as experimenting with innovative methods early in development cycles.
Domain Knowledge: Serves as a key subject matter expert within the broader company environment, offering insight into the data foundations of the team’s products and promoting continuous learning through active involvement in internal guilds.
Business Engagement: Works closely with commercial teams and data product stakeholders to clarify needs around data delivery and ensure visual outputs meet business expectations.
Data Transformation & ELT: Designs and refines ELT workflows to ensure smooth, reliable data movement into the platform. Applies data validation, enrichment, and hygiene techniques to uphold quality standards for analytical outputs.
Data Modelling & Architecture: Aligns with architectural frameworks and best practices, working with analysts and scientists to define requirements and build optimised models and storage strategies that support efficient querying and analysis.
Prototyping Visual Solutions: Provides support to product teams in refining and building interactive dashboards and other visual presentation tools as part of broader data delivery.
Performance Tuning & Optimisation: Continuously reviews and enhances pipeline performance, resolving bottlenecks, addressing integration complexities, and improving data quality through proactive monitoring.
Data Quality: Defines clear expectations for data accuracy across deliverables and works alongside QA to implement automated quality checks, surfacing results through observability tools.
Data Governance & Security: Ensures adherence to the company's data governance, privacy, and compliance frameworks, including applying appropriate controls for access, encryption, and retention, and following architectural oversight processes.
Support & Monitoring: Ensures observability standards are met across all data products, working with operations and platform teams to establish appropriate metrics and monitoring dashboards for system health and stability.
Collaboration & Documentation: Engages proactively with other technical teams—analysts, software developers, and data scientists—to deliver fit-for-purpose data solutions. Maintains thorough documentation and translates complex technical concepts into accessible formats for varied audiences, including presenting to wider internal groups.
Continuous Improvement: Keeps pace with the evolving data landscape, identifying opportunities to modernise tooling, automate workflows, and adopt innovative practices. Collaborates with the team to support feature evolution and remains an active contributor to internal knowledge-sharing communities.
Ways of Working: Leads engineering engagement in delivery activities by refining work items, distributing tasks within the team, defining and owning user stories, providing updates during stand-ups, and managing delivery expectations. Also supports improvements to CI/CD and related processes.
WHAT WE ARE LOOKING FOR:
- ATTENTION! THIS POSITION IS FOR PORTUGAL OR BRAZIL BASED ONLY
Lumenalta (formerly Clevertech)
ALDIA
SynergisticIT
Recharge
Rad AI