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Day 124
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São Paulo, SP, Brazil
Open 4 months, first seen by us 124 days agoWork setup in the employer’s posting: RemoteFrom the employer’s posting
Employment type in the employer’s posting: ContractFrom the employer’s posting
Develop and improve services to load, transform and consume data
Support data science and operations projects that rely on data infrastructure
Improve scalability, resource-efficiency, latency and flexibility of data services
Develop and improve services to load, transform and consume data
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
Sound knowledge of data manipulation programming, particularly Python
Experience as software engineer in Datawarehouse / ETL projects
Sound knowledge in relational and non-relational databases (PostgreSQL, MongoDB)
Experience in technologies like Kafka, Cassandra, Airflow and Spark
Experience with data visualization tools (Tableau, Metabase, Power BI)
A product mindset, in which engineering costs are measured against the benefits to our product
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;
· Sound knowledge in relational and non-relational databases (PostgreSQL, MongoDB) · Experience in technologies like Kafka, Cassandra, Airflow and Spark Company Description
· 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;
· 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
Adimplere is a debt collection Fintech, with a tech-intensive approach to deliver great recovery performances to our partners and a seamless experience to the customer.
In the employer’s words · Read in context
Open 4 monthsWe first saw this posting 124 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 124
Up longer than most. Similar jobs usually come down between day 6 and day 54.
From 10,764 similar postings that came down. Coming down is not always a hire.
1 open job
Hiring recordCheck the employer’s posting for the current role and application details.
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We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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
About Adimplere
Adimplere is a debt collection Fintech, with a tech-intensive approach to deliver great recovery performances to our partners and a seamless experience to the customer. The company aims to maintain itself as the top performer in the market and continuously improve the credit collection efficiency. The Brazilian debt collection market is currently dominated by outdated players whose operations are focused on massive and inefficient call centers. Adimplere outperforms the traditional players by using a data-driven operation and artificial intelligence on several steps of its processes.
Our headquarter is located in São Paulo, with a top-notch team of professionals. Adimplere has a challenging working environment and a meritocratic culture.
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São Paulo, SP, Brazil
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