Data Engineer
Summary
Data Engineer at Adimplere, a Brazilian tech company rethinking debt collection, building world-class data infrastructure: developing services to load, transform and consume large datasets (conversation texts, images, behavior events) that power ML, dashboards and customer reporting. Core stack includes Python, SQL/NoSQL databases, Kafka, Airflow and Spark.
Our Data Chapter
Adimplere is a technology-oriented company that is rethinking debt collection in Brazil. We are looking for outstanding Data Engineers to help us build a world-class data infrastructure.
We believe in:
· Strongly collaborative teams;
· Enthusiasm for building new products features and improvements;
· Environment which supports professional development. Though very pragmatic, we do study a lot and we promote discussions across all seniority levels (You may discuss Multicolumn Indexing with the CEO occasionally);
· Constructive feedback culture, either formal and informal.
What are the challenges a Data Engineer will face at Adimplere?
· Develop and improve services to load, transform and consume data, employing cutting edge technologies and the best tools available in the market;
· Interact with data science and operations PMs to keep a deep understanding of their business needs and support projects that rely on data infrastructure;
· A constant pursuit for improvements in aspects like scalability, resource-efficiency, latency and flexibility for our data services;
At Adimplere we have massive and complex datasets with conversation texts, images, user behavior events and operation data. We have a wide range of data applications like machine learning algorithms, data discovery, dashboards and periodic reporting to customers.
Requirements
There is not a single skill set to make valuable contributions, we are looking forward to meet people with diverse backgrounds. However, we believe you will be a fit for this position if some of these points are part of your profile:
· Sound knowledge of data manipulation programming, particularly Python;
· Experience as software engineer in Datawarehouse / ETL projects;
· Experience with data visualization tools (Tableau, Metabase, Power BI);
· A product mindset, in which engineering costs are measured against the benefits to our product;
· Sound knowledge in relational and non-relational databases (PostgreSQL, MongoDB)
· Experience in technologies like Kafka, Cassandra, Airflow and Spark