Your path to Senior Data Engineer

Data is the fuel of the modern economy and Data Engineers provide the necessary knowledge to extract as much knowledge out of it as possible – a key role!

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Opportunities and strategies to grow into a Senior Data Engineer role.

In the end, advancing your career is all about getting the right opportunities at the right time and a good portion of luck.

These are some interesting things going on in the Data Engineering space and you probably don't want to miss them.

Python Project for Data Engineering

This mini-course is intended to apply foundational Python skills by implementing different techniques to collect and work with data. Assume the role of a Data Engineer and extract data from multiple file formats, transform it into specific datatypes, and then load it into a single source for analysis.

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Data Engineering Project for Beginners - Batch edition

A real data engineering project usually involves multiple components. Setting up a data engineering project, while conforming to best practices can be extremely time-consuming.

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SQL Project for Data Analysis using Oracle Database-Part 3

In this SQL Project for Data Analysis, you will learn to efficiently write sub-queries and analyse data using various SQL functions and operators.

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Udacity Data Engineering Projects

Few projects related to Data Engineering including Data Modeling, Infrastructure setup on cloud, Data Warehousing and Data Lake development.

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DEDS - Data Engineering for Data Science

The European Joint Doctorate in "Data Engineering for Data Science" (DEDS) is designed to develop education, research, and innovation at the intersection of Data Science and Data Engineering

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Apache Spark

Spark is a fast and general cluster computing system for Big Data. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Spark Streaming for stream processing.

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DataSF

Search hundreds of datasets from the City and County of San Francisco. Or browse on the data catalog

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Netflix Data Engineering

This repo is created to content the presentation, code and data for the Data Engineering WiBD Workshops at NFLX.

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Growing into a Senior role pays off – $30,000 per year to be exact.

Not only is the progression from individual Data Engineer to a Senior role a natural progression, it also makes all the difference in your wallet.

On a global average, Senior Data Engineer receive a $30,000 salary hike when they go from individual contributor to senior personnel.

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Courses to practice crucial Data Engineering skills.

These days, courses are no longer a sequence of videos. They are usually accompanied by projects and a learning community, keeping you accountable and on the path.

Our experts recommend these courses, from free selections to paid programs.

Advanced Database Administration

Advanced Database Administration

Learn the fundamentals of administering relational database management systems, including managing concurrency and creating objects in the database

Data Engineering

Data Engineering

Learn to design data models, build data warehouses and data lakes, automate data pipelines, and work with massive datasets. At the end of the program, you’ll combine your new skills by completing a capstone project.

Data Engineering on Google Cloud platform

Data Engineering on Google Cloud platform

End to end batch processing,data orchestration and real time streaming analytics on GCP

Data engineering and smart analytics

Data engineering and smart analytics

The need for data analysis skills grew by 86% from 2013 to 2018. 1 Become data-driven with Google Cloud. Leverage data and gain real-time insights that improve your decision-making and accelerate innovation. Learn how to design and build data processing systems.

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Take the next step with a
Data Engineering mentor

There is no better source of accountability and motivation than having a personal mentor. What used to be impossible to find is now just two clicks away! All mentors are vetted & hands-on!

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Conversational AI Engineer at IBM
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📝 TL;DR Me -> Applied ML @IBM. ex-ML Eng @SoundHound. ex-instructor @University of Toronto. Services -> One-off sessions (CV review, practice interview, etc.) and mentorship program. 👋 About Me Hi there, my name is Reza and I am a Conversational AI Engineer @IBM Watson. Previously a Machine Learning Engineer @SoundHound …
$320 / month
Senior Data Scientist & Machine Learning Engineer at IBM
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As Managing Consultant for Data Science and Machine Learning, I develop end-to-end machine learning solutions for my clients and help them get business value with their data.
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Data Scientist at Google
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I am a Data Scientist with 7+ years of rich industry experience currently working in Google on the Google Maps team. Me and my team works on building counter abusive models to keep the Geo surface free from abuse. I completed my Masters from UIUC in CS with a specialisation …
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Data Science Manager at Google
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Data Scientist with 10+ years of experience scaling data at top tier Silicon Valley companies. I’ve led projects spanning from Machine Learning, Data Engineering, to A/B Testing and Data Visualization. My professional experience has equipped me with an understanding of a) How to leverage data for different functions and projects …

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Best books to further your Data Engineering understanding.

A well-written and thorough book can be an amazing path to build deeper understand and also act as a handbook as you discover the internet's vast resources.

These are our and our experts top picks to get started building career-relevant skills.

Data Engineering Cookbook

Data Engineering Cookbook

Five types of content are in this book: Articles the author wrote, links to his podcast episodes (video & audio), more than 200 links to helpful websites he like, data engineering interview questions and case studies.

Database and Expert Systems Applications

Database and Expert Systems Applications

The Database and Expert Systems Application -DEXA - conferences are mainly oriented to establish a state-of-the art forum on Database and Expert System applications. But Practice without Theory has no sense, as Leonardo said five centuries ago. In this Conference we try a comprornise between these two complementary aspects. A total of 5 sessions are application-oriented, ranging from classical applications to more unusual ones in Software Engineering.

The Data Warehouse Toolkit

The Data Warehouse Toolkit

One of the most dramatic new developments in database design, the dimensional data warehouse is a powerful database model that.significantly enhances managers' ability to quickly analyze large, multidimensional data sets. Written by the leading proponent of this revolutionary new approach, this valuable book/CD toolkit outfits you with all the nuts-and-bolts information you need to design, build, manage, and use dimensional data warehouses for virtually any type of business application, as well as software for querying dimensional data warehouses.


Designing Data-Intensive Applications

Designing Data-Intensive Applications

Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?

Advanced Topics in Database Research

Advanced Topics in Database Research

Advanced Topics in Database Research is a series of books on the fields of database, software engineering, and systems analysis and design. They feature the latest research ideas and topics on how to enhance current database systems, improve information storage, refine existing database models, and develop advanced applications.

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The Data Engineering must-reads you shouldn't miss.

Key articles and posts of industry experts can help you get a better picture of what you are getting into.

In our opinion, these are some must-reads you really shouldn't miss.

The Path to Becoming a Data Engineer

The definitive guide to help you become a data engineer.

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A Strategic Approach to Data Quality

“To tackle today’s Data Quality challenges, you need a more strategic approach,” said Nigel Turner, Principal Consultant, Global Data Strategy.

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What Are The Benefits Of Cloud Data Warehousing And Why You Should Migrate

Since then the concept has evolved and taken on a life of its own. Increasing challenges and complexities of business have forced data warehousing to become a distinct discipline. Over the years this has led to best business practices, improved technologies, and hundreds of books being published on the topic.

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Harness the power of data literacy through democratizing data

Author Jordan Morrow weighs in on enterprise strategies to improve democratizing data through expanded use of BI and augmented analytics.

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The Future of the Data Engineer

Is the data engineer still the “worst seat at the table?” Thoughts on the past, present, and future of tooling, processes, and culture in our industry.

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Essential Responsibilities and Skills of a Data Engineer

Quite often, it is observed that people, as well as organizations, are ignoring essential skills for a Data Engineer. In this detailed article, I will cover all the essential skills to become a Data Engineer.

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10 Data Literacy Skills to Become a Data Citizen

Data literacy skills are increasingly top-of-mind for corporate learning and development initiatives. A recent webinar guest, Daryl D’Cruz, shared, “data literacy skills are the building blocks of digital transformation.”

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Get the help you need & advance your career

Where will you stand in the digital revolution and uprising of the data engineering role? We say it's time to prepare – pick up some data engineering skills with our vetted mentors!