How to succeed as a Data Engineer - freelance or perm
![](https://api.free-work.com/media/cache/resolve/blog_post_image_large/how-to-succeed-as-a-data-engineer-freelance-or-perm-vEm1DEEvih0pS8m5.png)
Forget our own database, a quick search on LinkedIn shows just over 1,300 live Data Engineer roles, 1,200 posted in the last month, 500 in the last two weeks and 200 in the last 24 hours alone!
Almost needless to say, the role of a Data Engineer is becoming increasingly more important – especially with the growth of the data centre market which we can attest to.
In this article, exclusively for Free-Work, I will explore the role of the data engineer, how to succeed as a data engineer, and the skills (hard and soft) requires to be a successful data engineer, writes Pendy Hou, senior delivery team leader at recruitment agency First Point Group.
What is a Data Engineer?
In its simplest form, the role of a data engineer is to design, construct, and optimise systems for data collection, storage, access, and analytics at scale.
A data engineer’s key responsibilities can include (but are not limited to) creating data pipelines that transform data into usable formats for data scientists, applications, and other stakeholders.
How to succeed as a Data Engineer
Data engineers play a crucial role in both building tools to access raw data and managing and organising that data.
A data engineer monitors trends or inconsistencies that could impact business goals. As a highly technical position, the role of a data engineer requires expertise in areas such as programming, mathematics, and computer science.
However, data engineers also need ‘soft’ skills to effectively communicate data trends within the organisation and help the business utilise data.
What are a data engineer’s common responsibilities?
Some common responsibilities of data engineers include:
Developing, constructing, testing, and maintaining data architectures.
Acquiring and processing data.
Identifying ways to enhance data reliability, efficiency, and quality.
Preparing data for predictive and prescriptive modelling.
Here, and tied to these four, it’s important to add that a good data engineer, on a freelance basis or a full-time must:
Be flexible: A good contract data engineer should be flexible in terms of moving location and type of company - this will put you in good stead.
Know your value: A good contract data engineer should understand their market rate and be able to justify it.
Hard /technical skills needed to succeed as a Data Engineer
Data engineers whether freelance or full-time need a strong technical skillset, including expertise in SQL Database Design, and proficiency in multiple programming languages.
Effective communication skills are also essential, as data engineers collaborate across departments and align data strategies with business objectives.
Data engineers often build algorithms to access raw data and develop dashboards and reports for stakeholders.
In larger organisations, data analysts or scientists can sometimes assist in understanding data, while smaller companies may rely on data engineers to fulfil both roles.
Top 8 hard tech skills for data engineers
Either way, data engineers need a combination of technical and soft skills to succeed.
Here are some essential technical skills for data engineers:
Coding: Proficiency in programming languages like Python, Java, Scala, and SQL is crucial for data engineering positions.
Data warehousing: Familiarity with data warehousing solutions such as Panoply or Redshift is imperative for managing and analysing large amounts of data.
ETL (Extract, Transform, Load) tools: Data engineers work extensively with ETL tools to process and move data efficiently.
Machine learning: Basic understanding of machine learning concepts helps in data preparation and modelling.
Database systems: Knowledge of both SQL and NoSQL databases is essential for building and managing data systems.
Operating systems: Intimate understanding of operating systems like macOS, Windows, Linux, Solaris, and UNIX is vital.
Distributed systems: Basics of distributed systems contribute to effective data engineering.
Algorithms and data structures: Understanding algorithms and data structures enhances data processing and optimisation.
Data Engineer Job? Sure, you’ll need…
The breadth of a data engineer’s role in H2 2024 often has multiple responsibilities, ranging from developing and maintaining data architectures, to preparing data for predictive and prescriptive modelling.
A successful data engineer combines technical knowledge with the ability to communicate and adapt, ensuring you can meet the demands of the data-driven market. As technology evolves and expands, the role of the data engineer on both a contract and permanent basis will only become more pivotal, making it a rewarding and promising career path.
![](https://statics.free-work.com/blog/posts/more_images/pendy-h-6662c6a939cfd695983929.png?
ixlib=rb-1.2.1&ixid=MnwxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8&aut
o=format&fit=crop&w=1712&q=80)
Comment
Log in or create your account to react to the article.