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unique chance to become a senior data engineer in the data & analytics services team where you will be working on data lake and data warehousing projects. This role will be responsible for analyzing business and system requirements and defining the optimal data strategy to meet them. The role holder will design and implement data acquisition strategies and own and extend the business’s data pipeline through the collection, storage, processing, and transformation of large data sets.
further responsibilities of the senior data engineer will include:
* building scalable, performant, supportable, and reliable data pipelines. Enjoy optimizing data systems and building them from scratch.
* setting up new and monitoring existing metrics, analyzing data, and collaborating with other data & analytics team members to identify and implement system and process improvements.
* supporting the collection of metadata into our data catalog system, ensuring data is maintained and cataloged accurately.
* defining and implementing a devops framework using ci/cd.
* working closely with big data architects, data analysts, data warehouse engineers, and data scientists.
* supporting and promoting an agile way of working using the scrum framework.
* coaching a small team of junior data engineers (2 people).
what will you need?
to succeed in this role, you should have excellent analytical skills working with structured, semi-structured, and unstructured datasets, expert sql knowledge, and experience with relational and no-sql database systems.
you must have expert-level programming skills in python/pyspark, and experience in java/scala programming is a plus.
experience with data warehousing for large, complex datasets—defining, building, and optimizing data models based on use case requirements—is preferred.
* university degree in computer science, information systems, statistics, or related field;
* minimum 5-7 years of experience in it;
* minimum 3-5 years of experience as a data engineer;
* experience with data lake/big data projects in cloud (preferably ms azure) and/or on-premise platforms:
* azure stack: adls gen2, databricks (proven experience is a big plus!), eventhub, stream analytics, synapse analytics, aks, key vault;
* on-premise: spark, hdfs, hive, hadoop distributions (cloudera or mapr), kafka, airflow (or other schedulers);
* designing and building lakehouse architectures in parquet / delta and synapse serverless or databricks sql (unity catalog knowledge is a big plus);
* ability to develop, maintain, and distribute modularized code;
* experience with devops frameworks;
* understanding of software development lifecycle, source code management, code reviews, etc.;
* experience in root cause analysis of data and processes to answer business questions and identify improvements;
* experience in building data transformation processes, data structures, metadata, dependency, and workload management.
you should have:
* ability to collaborate across teams, geographies, stakeholders, and levels of seniority;
* energetic, enthusiastic, and results-oriented personality;
* customer focus with a drive for continuous improvement;
* motivation and ability to act as a consultant in data engineering projects;
* ability to work independently and as part of a team;
* strong determination to overcome the complexities of developing and supporting data pipelines.
language requirements:
* fluent spoken and written english;
* fluent in spanish or portuguese is a plus.
seniority level
* mid-senior level
employment type
* full-time
job function
* information technology
industries
* staffing and recruiting
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