Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. This title means an individual who can bridge the gap between a data engineer and data science at some companies.

Data Engineer 98

Data Engineer Data Engineering Engineering Hadoop 98

Meltano

OCTOBER 5, 2022

With DevOps best practices applied to data workflow, data engineers can speed up the entire data management cycle by using automation, all while giving them control over their pipelines so any irregularities such as duplicate data are immediately spotted and fixed.

Data Engineer 52

Data Engineer Data Engineering Engineering Raw Data 52

Netflix Tech

OCTOBER 18, 2022

With the high growth of workflows in the past few years?—?increasing increasing at > 100% a year, the need for a scalable data workflow orchestrator has become paramount for Netflix’s business needs. As the usage increased, we had to vertically scale the system to keep up and were approaching AWS instance type limits.

Java 85

Java Data Machine Learning Systems 85

dbt Developer Hub

OCTOBER 14, 2021

Anna (dbt Labs Director of Community), does a phenomenal job connecting this week's events in the latest issue of the Analytics Engineering Roundup. Things to Watch ? What's missing? Spreadsheets? Okay you had to be there. Luckily you still can! Check out the recording.

Metadata 52

Metadata BI Software Engineer Software Engineering 52

Monte Carlo

OCTOBER 1, 2024

“Monte Carlo’s automated monitors have given us the scale and coverage we need to build trust with our internal and external data consumers, but we can also set custom, granular alerts to ensure service levels are being upheld,” said Matt Wurst, Senior Director, Software Engineering at Accolade.

Database 52

Database Metadata Software Engineer Software Engineering 52

Netflix Tech

NOVEMBER 20, 2023

This enables auto propagation of backfill data in multi-stage pipelines. Netflix Maestro Maestro is the Netflix data workflow orchestration platform built to meet the current and future needs of Netflix. Basically, the range derived from the change data indicates the dataset to be re-processed.

Process 88

Process Data Pipeline Datasets SQL 88

phData: Data Engineering

MAY 11, 2023

Traditional Software Development Lifecycle (SDLC) makes assumptions about the organization of work that are no longer always true in Low and No Code working patterns. Jargon such as “directed acyclic graph” used by software engineers is unhelpful and even damaging to the business stakeholder conversations.

Coding 52

Coding Software Engineer Software Engineering Project 52

Monte Carlo

JULY 27, 2023

The Expertise and Skills You Bring Engage with product owners and development leads to create testing strategies Identify areas of improvement in data quality processes and propose solutions to enhance data accuracy and reliability. Experience with data processing concepts like mapping documents and complex data relationships.

Engineering 52

Engineering Healthcare Data Warehouse Scala 52

Databand.ai

DECEMBER 29, 2022

Follow Priya on LinkedIn 6) Niv Sluzki Director of Engineering at Databand Niv is dedicated to solving data health and data quality issues for code-intensive data engineering teams. Niv also contributes to hatochna.com , where he writes about engineering culture and leading a product-driven engineering team.

BI 52

BI Consulting Data Science Data Governance 52

Monte Carlo

MARCH 24, 2021

How to build a data pipeline? How to clean, transform, and model your data? How to prevent broken data workflows before you get that frantic call from your CEO about her missing data?

Data Engineer 40

Data Engineer Data Engineering Engineering Software Engineer 40

DareData

NOVEMBER 28, 2023

These practices and methodologies are commonly known as MLOps, short for Machine Learning Operations and they bridge the gap between data science and software engineering, ensuring the pillars of experimentation: reproducibility, performance, scalability and monitorization. But that is not all!

Data Science 52

Data Science Medical Machine Learning Data 52

Ascend.io

MARCH 17, 2023

In fact, it’s been a recurring theme in software engineering. Their engineers discovered that the same Javascript code was being sent thousands of times to each individual browser or app, creating redundant traffic and blocking faster performance. Value Catching data problems in real-time avoids costly reruns and delays.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

Ascend.io

MARCH 17, 2023

In fact, it’s been a recurring theme in software engineering. Their engineers discovered that the same Javascript code was being sent thousands of times to each individual browser or app, creating redundant traffic and blocking faster performance. Value Catching data problems in real-time avoids costly reruns and delays.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

Monte Carlo

SEPTEMBER 20, 2022

Prefect, the company behind the eponymous data workflow management system, is on a mission to make coordinating data flows easier. Pitched as “air traffic control for your data,” Prefect supports the likes of Amazon, Databricks, and Adobe just to name a few.

Big Data 52

Big Data Data Warehouse Data Data Governance 52

AltexSoft

MARCH 14, 2023

A Modern Data Stack (MDS) is a collection of tools and technologies used to gather, store, process, and analyze data in a scalable, efficient, and cost-effective way. Software engineers use a technology stack — a combination of programming languages, frameworks, libraries, etc. —

IT 59

IT Data Warehouse Data Governance Data Lake 59

phData: Data Engineering

JANUARY 3, 2022

Software engineering practices define how to reliably and effectively build software and data products, delivering value faster to your customers. Table of Contents How Impactful is Your Data? What’s Data Strategy? Roadmapping The Data Strategy Journey How Do Software Engineering Principles Solve This?

IT 52

IT AWS Software Engineer Software Engineering 52

DataKitchen

MARCH 16, 2023

Additionally, investing in data testing and observability and implementing DataOps principles can help streamline data workflows and reduce the time it takes to complete data analytics projects. Which metrics should I use, exactly? The world of team metric measurement is confusing.

Data Analytics 52

Data Analytics Manufacturing Data Process 52

Ascend.io

FEBRUARY 25, 2025

Keep it simple: If your data workflow spans cloud functions, databases, and more, you might need custom scripts or adapters in your pipeline. Consider simplifying your data stack with a single, end-to-end solution that empowers you to execute your scripts and queries from a unified platform.

Data Pipeline 52

Data Pipeline Data SQL Coding 52