Data Engineer

hace 3 semanas

Barcelona, España Nielseniq A tiempo completo

NIQ is the world's leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth.
In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach.Founded in Barcelona in 2001, Netquest is the data collection provider of choice for the Market Research Industry.
A tech-driven company built on a robust and engaged panel and a strict quality standard (ISO 20252).
We make possible a truly 360 degrees view of today's consumers collecting behavioral and declarative data from a single source, our panelists, in 23 countries across the globe.
Leveraging our data, savvy researchers better define winning strategies based on an in-deep understanding of consumers' preferences and behaviors.Job DescriptionAs a Data team, we cover the three main specialties in the data field: Data Science, Data Analytics, and Data Engineering.
While our current needs are well met in each field, we are looking to strengthen our Data Engineering capabilities by adding a skilled Data Engineer to our team.
We seek a person who brings practical experience and enthusiasm to help drive our data initiatives forward.We are currently developing a robust data strategy inside Netquest.
We are looking for a collaborative team player who enjoys working with others and interacting with various departments.
This role involves understanding different stakeholders' needs, sharing decisions with the team, and explaining data solutions clearly.Key AccountabilitiesThe data engineer is expected to work within their team scope and contribute to the harmonization and improvement of solutions across the organization.The data engineer is accountable for sharing knowledge with other engineers during pair programming/pair work, when sought for advice, during code reviews, and by participating in Communities of Practice.The data engineer is responsible for bringing together technical assets from different disciplines within their cross-functional team and fostering a common solution approach among team members with diverse technical backgrounds.QualificationsExperience in designing and implementing data pipelinesAbility to address problems with scale-up and scale-out approaches and combine them in data pipelinesUnderstanding of Data Architecture principlesAwareness of Data Governance practicesConsideration of economic aspects related to the operability of data pipelinesMaintenance of data integrity during reprocessingUnderstanding how customer data deliveries (internal or external) are affected by software changesFamiliarity with data design patterns and best practicesKnowledge of data modeling, data schemas, and their evolutionAwareness of data transformation design patternsFocus on data integrity in crafting data pipelines, including monitoring data health and state of intermediate data and alerting mechanismsDesigning Quality Control/Validation processes / Quality GatesTechnologies and StandardsProficiency in Python and SQLFamiliarity with scheduling tools like Apache AirflowInterest in Big Data solutions, such as Apache SparkUnderstanding of Data Engineering techniquesAbility to maintain and extend processes and functionalitiesKnowledge of application packaging and delivery mechanisms, including CD/CI best practices and security concernsAbility to integrate partial solutions and RnD results into production-ready data pipelinesExperience in building and operating infrastructure (e.g., for testing purposes)Ability to support operational questions for production environmentsUnderstanding of cloud infrastructure and services for setting up and maintaining data pipelines (e.g., AWS)Advising on data transformation workflow designs and optimizations focusing on cost, performance, and delivery mechanisms (streams/increments/etc.
)Additional InformationFlexible working environmentVolunteer time off #J-18808-Ljbffr

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