What does a data engineering project include?

Data pipelines, orchestration and data quality for analytics and AI, with tests and monitoring from the start.

How is data pipeline quality measured?

With data tests and monitoring of every run: freshness, volume and validity, with alerts when something drifts.

Where does BlueliftAI work?

With companies in the United States and Latin America, remotely.

Data Engineering

Data that arrives on time, pipelines that wake nobody up.

We build data pipelines and platforms that turn raw data into decisions. Robust, monitored, boring to maintain.

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Data warehouse
Data pipelines
Analytics

From raw data to decisions

01
Sources
ERP, spreadsheets and APIs
02
Pipelines
clean and transform
03
Decisions
dashboards and models

What we do

Pipelines and ETL/ELT

Ingestion, transformation and loading with tests and alerts, not faith.

Warehousing

Dimensional modeling, data marts, consumption layers for BI and analytics.

Integrations

Connectors to your sources — APIs, SaaS, databases — built to last.

Real-time analytics

Streaming and operational dashboards when "yesterday" isn't enough.

Real experience

40+ data integrations built with the Meltano SDK — Python pipelines processing high-volume data with Pandas, Dask and Apache Parquet, several open-sourced on GitHub.

Meltano SDK
Python
Pandas
Dask
Apache Parquet
GitHub