Data Engineer

Data engineering is the process of discovering, designing, and building the data infrastructure to help data owners and data users use and analyze raw data from multiple sources and formats. This allows businesses to use the data to make critical business decisions. You can revisit the definition of data engineering here. If you want to dig a little deep we recommend taking a look at the four fundamentals of data engineering:

1. Data discovery and lineage
2. Data ingestion
3. Data processing
4. Data quality

Unleash the power of data by building an AI-powered modern data architecture

Discover, understand, trust, and access relevant data to generate business value

Replicate and ingest data from applications, databases, streaming sources, and files using a simple, wizard-driven experience.

Build, deploy, and operationalize low-code data pipelines at scale

Profile, cleanse, standardize, and enrich all data using an extensive set of prebuilt data quality rules.

Open, embeddable, and extensible headless data management for data engineers

Build, deploy and monitor your AI/ML models at scale