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Senior Data Engineer
TractianPredictive Maintenance company
On-site
Sapphire Ventures
General Catalyst
Next47
NGP Capital
Y Combinator
About the role
- •Analytics at TRACTIAN The Data Engineering team is responsible for building and maintaining the infrastructure that handles massive datasets flowing through TRACTIAN’s systems.
- •This department ensures the availability, scalability, and performance of data pipelines, enabling seamless access and processing of real-time and historical data.
- •The team’s core objective is to architect robust, fault-tolerant data systems that support everything from analytics to machine learning, ensuring that the right data is in the right place, at the right time.
- •What you'll do As a Data Engineer, you will build data pipelines that enable data extraction, loading and transformation for several contexts.
- •The goal is to have a reliable, available and trustworthy system that backbones the entire analytics pipeline.
- •The challenges may vary from large datasets to high data throughput systems, not being reduced to a small set of techniques for data handling.
- •You will also lead initiatives on data pipelines reliability and observability.
- •Responsibilities Develop and maintain scalable data pipelines and ETL processes.
- •Design, implement, and optimize existing data extraction and loading processes with adequate data engineering design patterns.
- •Lead data engineering reliability and observability, increasing analytics team awareness of the data flow processes before it becomes an issue.
- •Collaborate with backend and analytics engineers in a holistic data engineering process, loading data accordingly with the technical requirements.
- •Ensure data quality and consistency across various sources by implementing data validation and cleansing techniques.
- •Work with cloud-based data warehouses and analytics platforms to manage and store large datasets.
- •Monitor and troubleshoot data pipelines to ensure reliable and timely delivery of data.
- •Document data processes, workflows, and best practices to enhance team knowledge and efficiency.
- •Create dashboards as data products as internal Requirements Bachelor degree in Data Science, Statistics, Computer Science, or a related field.
- •Advanced English and Portuguese. 2+ years of experience in Data Engineering or Analytics.
- •Highly experienced in SQL and database management systems such as PostgreSQL and Clickhouse .
- •Strong understanding of data warehousing concepts and experience with ETL tools (e.g., Airflow, dbt).
- •Strong experience with programming languages such as Python with modern data stack for data engineering (e.g.
- •DuckDb, Polars...) Experience with streaming tools (e.g.
- •Experience with cloud-based data platforms like AWS Redshift.
- •Experience with GoLang/Rust is a plus.
- •Experience with observability tools is a plus (e.g.
- •Datadog, Grafana)