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Advice by a Data Specialist on How to Secure Your Next Role

15 days ago by Andy Davies
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About the author

Andy Davies has worked in data related roles for twenty years across a range of industries and business sizes. He currently works as an Analytics Engineering Manager building modern data infrastructures with a passion for coaching and mentoring team members to grow in their skills and careers.

At Gravitas, we are passionate about helping people find new jobs and providing guidance to help people progress their careers. Today, we have the pleasure of hearing from one of our own technology candidates, who has had a successful data career, and is looking to help others to do the same. Read Andy’s advice and tips below and see how it can help your own career from someone who has lived through it. 

How the progression of data infrastructure has evolved job roles

The data landscape has changed a lot for data professionals in a short space of time. 

Twenty years ago, many companies still had their relational databases hosted on premises in a server room or in managed server racks in a nearby data centre, still close enough to drive to for conducting backups and maintenance.

But around fifteen years ago Amazon Relational Data Service (RDS) and Microsoft Azure SQL Database were launched, marking the birth of cloud data infrastructure. Now we have mature Azure, AWS, Google cloud platforms each with their own numerous offerings of cloud hosted and managed relational, document and graph databases. 

As technologies have developed, so have individual contributor roles, evolving to match. Managed cloud data warehouse products such as Databricks, Snowflake, AWS Redshift or Google BigQuery with configurable scaling have encouraged a new generation of skills and engineer roles to replace some of the traditional roles like Database Administrators. Traditional data warehousing and data modelling with a focus on normalisation and batch workloads has transitioned to the data lakehouses and data modelling with a trend towards denormalization and event driven workloads. 

Whilst there has never been a more exciting time to become a data professional, staying up to date across the breadth of roles and technology change, that encompasses the “modern data platform”, remains a challenge and can be daunting to many; particularly as so many aspects of our lives are intertwined in the production and consumption of data. 

The reasons for why we start looking for a new role vary for us all. Some of us tire of our workplaces, clash with our line managers, experience progression or salary stagnation. For others they have a plan. For some a required change of direction. Sadly, all too often, we’re impacted by redundancy.

With so much technological and process change and an ever-growing selection of tools and platforms what strategies are available to us to make our next job search as smooth as possible?

Taking stock of your current work situation

Ideally the company where you work will be, as part of their data strategy, bringing in new tools and evolving roles, opening up new roles, and providing training to develop you as an individual. However, we’ve all worked in companies where even with these best efforts, budgets for new tools get squeezed, and project deadlines take over and before you know it five years has passed and you’re still working with the same technologies, and it feels like everyone else has moved on. 

Don’t let this deter you. Set a reminder and regularly spend an hour or few to take stock yourself. What does “taking stock” mean? Create and maintain a simple matrix of job role variations and key technologies like this one by datacamp. Then regularly review and update. Identify where you feel comfortable. And where you might have gaps in your knowledge or understanding.

Signup to some engineering blogs that cover aspects data industry. Many leading companies, such as Uber, AirBnb, Monzo and Etsy, produce tech or engineering blogs specifically covering changes in their data infrastructure and unpack system designs. Medium is another community that is regularly contributed to by a wealth of data professionals. Content creators are often writing about the latest trends so these articles will give you a good sense of what’s current or being considered from a skills perspective and a technology or methodology perspective. Follow some relevant tags on these blogs; data engineering, analytics engineering, data science, data ops.

Another approach is to spend some time reading job descriptions and keeping fresh with what roles and technologies the market is hiring for now. Seems obvious but it’s not always that easy. Pick a handful of well know companies across a range of industries, e.g. banking, fashion, retail, supermarkets, and review their job listings or team member job titles. LinkedIn is a good place to start and not only provides a lot of job listings, but also allows you to look at employee profiles to gauge the job roles recently hired. Make use of search syntax to tailor your search, e.g. data+engineering for a wider search or “data engineer” for a specific search.

Intentionally develop your focus

What you may quickly realise is you don’t have the time or opportunity to become an expert in all the possible tools, methodologies, and languages. Should you learn about Azure and their data tools? Or AWS and theirs? Even within a single cloud platform you have multiple tools at your disposal. This is where taking stock helps and gives you a sense of where to focus. You can’t learn them all.

Hopefully by taking stock you’re able to identify some common technologies where you’re already experienced. Consider where there are gaps in your learning or if you want to transition from one role to another. For example, working your way down a “learning channel” will help, e.g. Python, Pandas, PySpark, PyTest, PyTorch & NumPy. This gives you flexibility to apply for jobs within the fields of Data Engineering, ML Engineering, Data Analysis and Data Science without a significant shift in technology or language.

Know the equivalent for each cloud platform but it’s ok to be an expert in one. For example, you may already be an expert in AWS Redshift but job roles are asking for BigQuery experience. Spending a day or two with some “fundamentals training courses” should give you a good degree of knowledge that allows you to talk confidently during an interview process about how you can translate your skills across to Google’s BigQuery or Azure SQL Server, for example. Most companies don’t expect you to have used every tool, it’s more important to know when and why you might use one type of tool.

The right network & support makes a big difference

Securing your next role can be stressful, frustrating, disappointing, and sometimes drawn out. Having the right people around you can be a huge benefit, whether the support and encourage of trusted friends, referrals from former colleagues, advice from mentors, or the experience of specialist recruiters.

There are a lot of recruitment companies or individuals who will be offering their services to you. And consequently, you can be overwhelmed with offers that distract instead of help. Good recruitment companies though know the market, have valuable contacts and relationships, and can get you that all important “foot in the door”. 

Industry or role specialist recruiters, like Gravitas, can understand what you are looking for and work with you on that plan and tailor a search to your needs, skills, and experience.

They also advertise roles across Data on their website including ones like Data Engineer

Time to put your plan into action

In summary, you’ll find securing your next role much easier if you feel prepared and that you have a plan. Doing this proactively and regularly is a good mindset even if you aren’t actively looking for a new role. But if you’re only just starting your job search and feel overwhelmed about how out of date your CV is, or your experience and skills, please try not to worry. It’s never too late to start the process.

Apply an agile mindset to your job search and you will see success. Start with a small batch of applications. Be happy to fail fast as every process has its challenges. Try and understand where you can adapt and iterate and try again. Update your plan after each round of interviews, keeping track of what you think worked and what didn’t. Make use of your network but be strategic in who and when you use those opportunities. Be open minded and change the scope of your search if it makes sense to. 

Remember every application, every interview, gets you one closer to landing your next role.

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