Data & Analytics Technical Architect
Who are we?
AgileThought is a full-service software development and implementation firm staffed by passionate, experienced software professionals. Ok, that said, we are fanatical about what we do and believe happy employees make happy customers. We are a client services organization that thrives when our clients are pleased, and we’re always looking for individuals who care about finding the right solution and delivering that solution with the best quality so everyone walks away wanting more.
The Data & Analytics Technical Architect has a broad knowledge of data ingest and load scenarios and is an expert at transforming business requirements into the supporting dimensional models, reporting experience while meeting data refresh service level agreements. With an understanding of both Big Data and traditional architectures the Architect will lead delivery teams implementing these solutions in the cloud and in on premise environments. It’s also expected that the Architect understand machine learning techniques and processes to support Data Scientists that may be on the team.
Our goal is to have our clients view our delivery teams as a valuable partner in assisting them in achieving business value through the software solutions we provide.
Our goal is nothing less than creating unparalleled experiences for our clients and staff. Successful delivery of the intended solution is paramount, but enduring value lies in executing in a way that cannot be found with any other provider, and leaving the client with the best possible feeling of success.
What you’ll be doing:
- Works with product team to understand project requirements
- Build reusable code and libraries for future use
- Ensure the technical feasibility of design team outputs
- Optimize application for maximum speed and scalability
- Assure that all user input is validated before submitting to back-end
- Develop new and effective interactive design solutions on time and in scope
- Collaborate with Data Scientist team to deliver on new business initiatives and platform enhancements
How you’ll get the job done:
- Accountability for value in the work you perform and the service you provide
- Establish credibility by the sharing of knowledge related to your personal experiences and work with the team to maintain strong communication throughout each relationship
- Sticking to the game plan. If something gets committed, ensuring it gets done
- Making it your job to know the particular product being delivered and how it will provide business value
- Something will always come up, and it’s better to play like you’re catching up than to play like you’ve already won
- Whether it’s when you need help or when you’re unsure of an outcome, when in doubt, call out
- When something is standing in your way of providing a successful solution, you have the responsibility to bring the impediment to the attention of the team
- Stepping out of your comfort zone at times
- Taking pride in the work you have accomplished and showing it to the customer
- Avoiding the desire to take shortcuts at times instead maintain the consistency in how we approach solutions to ensure successful outcomes. Avoid the temptation to think that a difficult situation will be resolved simply by the passage of time and without the hard work of addressing root causes
What you’ll need to succeed:
- A strong understanding of dimensional modelling techniques
- Transactional, periodic, and accumulating fact table design patterns
- Additive and semi-additive measures. MDX or DAX expressions is a plus
- Slowly changing dimension principals and design
- ETL, partitioning, and change data capture load techniques
- The ability to design dimensional models that best lend themselves to a particular report type.
- A functional understanding of big data technologies
- Specific knowledge of the Hadoop ecosystem and how the various programs support big data movement and analytic
- Practical experience with at least one major distribution, i.e., Cloudera, Hortonworks, Microsoft HDInsight, etc.
- An understanding of how big data and traditional BI solutions integrate and some of the common concerns that should be addressed
- A high-level understanding of Machine Learning
- Major algorithm classes and training needs, e.g., supervised versus unsupervised
- ML process understanding, such as CRISP-DM
- An understanding of the data analytics technology landscape and vendor offerings with additional depth in the Microsoft stack
- Azure based analytics tools including Stream Insights, Azure Data Warehouse, Azure Analysis Services, Azure Data Factory, Azure Data Lake, Microsoft R Server, Azure ML, Power BI, and SQL Server technologies
- An understanding of the collaboration technology landscape
- Microsoft Office 365 and associated applications
- SharePoint 2013, 2016, and SharePoint Online capabilities matrix and a high-level understanding of the product roadmap
- An understanding on how Power BI and other analytics technologies compliment Office 365 and on-premise collaboration
- An understanding of hybrid collaboration topologies
- The ability to explain the Scrum development process and how team members contribute to this methodology
Great to Haves!
- Familiar with Audit/Assurance practices within the Big 4
Want to know more?
- Specifics about job such as travel requirements, full time/part time, extra benefits, etc.