Data Engineer and It's Tools

A data engineer is an IT worker whose primary job is to prepare data for analytical or operational uses. These software engineers are typically responsible for building data pipelines to bring together information from different source systems. They integrate, consolidate and cleanse data and structure it for use in analytics applications. They aim to make data easily accessible and to optimize their organization's big data ecosystem.

Data engineers work in conjunction with data science teams, improving data transparency and enabling businesses to make more trustworthy business decisions.

Data Engineer Role:

Data engineer focus on collecting and preparing data for use by data scientists and analysts. They are three main roles of data engineer as follows:

1. Generalists:

Data Engineer with general focus work on small teams, doing end-to-end data collection, intake and processing. They have more skills than other data engineer but less knowledge of system architecture.

A project a generalist data engineer might undertake for a small, metro-area food delivery service would be to create a dashboard that displays the number of deliveries made each day for the past month and forecasts the delivery volume for the following month.

2.. Pipeline - Centric Engineer:

These data engineers typically work on a midsize data analytics team and more complicated data science projects across distributed systems. Midsize and large companies are more likely to need this role. A regional food delivery company might undertake a pipeline-centric project to create a tool for data scientists and analysts to search metadata for information about deliveries. They might look at distance driven and drive time required for deliveries in the past month, then use that data in a predictive algorithm to see what it means for the company's future business.

3. Database - Centric Engineer:

These data engineers are tasked with implementing, maintaining and populating analytics databases. This role typically exists at larger companies where data is distributed across several databases. The engineers work with pipelines, tune databases for efficient analysis and create table schemas using extract, transform, load (ETL) methods. ETL is a process in which data is copied from several sources into a single destination system.

Data Engineer Tools

1. Python