Be prepared to spend a lot of time building up your professional network and brand - and never stop. When times are good, you'll feel like you can stop because opportunities are all over the place. When times aren't so good, you're going to want to avoid scrambling for more work.
That’s a very important point. Most of us will have a tendency to focus on the tech work but the real key to success is to always network and making connections. Also learn how to talk to C level execs because in the end they have control over the budgets and that’s where the money is. Also learn how to present your work. Doing a good job by itself is not worth much if nobody knows about it.
There's a huge difference between writing ETL to apply business logic vs. grab the data from a common API like Google Analytics. There's no tool in the world that can write all the logic you need to transform data the way your organization uses it unless you have an extremely simple, common use case.
What this article is really saying is that replicating your data from source apps shouldn't be manually coded. The harder part still needs someone to write code so business users don't need to.
Aptitive | Data & Analytics Consultant | Chicago, IL | ONSITE | Full-time
Aptitive is a Chicago-based data & analytics consulting firm. We were founded in 2013 with ~30 full time employees today. We are a tech-agnostic firm and work primarily with mid-size to large enterprises to provide business-driven, technical solutions.
Given the right experience level and fit, we're also looking to hire to lead practice areas and strategic partnerships.
* All experience levels are welcome, but ideally at least one year in development role
* Prior experience in consulting or customer-facing roles is preferred, but not required
* Understanding of the data and analytics ecosystem and design practices for data integration and data warehousing, including SQL development knowledge (and/or Python & .NET)
* Experience in Azure and/or AWS data platforms is preferred but not required
* Experience with ML algorithms and Python-based development for predictive models is a plus
Our work and technology stack varies by client, but we typically engage in project-oriented work (not contractor/staff aug models). We take a small team approach to project delivery, with a focus on quick deliverables and constant client feedback. Our work spans across technologies, but is usually a combination of data management, front-end analytics, custom data engineering, and data science solutions.
Good luck.