Join Ryen Gunning, Data Engineering Chapter Lead at Vista, as he reveals how a culture of engineering excellence is taking shape at Vista DnA and how this change is motivating our globally-distributed teams to build better quality data products.
At Vista DnA, our global, autonomous, cross-functional teams design and build valuable data products in a data mesh architecture. As a data-driven organization, trust in the quality and reliability of data products we deliver to our customers and internal stakeholders is at the core of our offerings.
The data mesh architecture suggests that we treat data as a product. Like any other software product, great data-product development is the key to a positive customer experience. But what exactly does “great product development” mean?
We decided to write down our shared beliefs, values, and mindsets to encapsulate DnA’s consensus of what we consider “great product development.” We call these values our “engineering excellence principles,” which help emphasize our commitment to quality and encourage a longer-term view into design and architecture.
These are not a set of “hard and fast rules” but rather help serve as a compass to help guide data product teams in pragmatic decision-making along their product development journey. This helps empower teams — not just data engineers — to discuss and take ownership of decisions at scale across our 30+ data product teams.
Vista’s Three Pillars of Engineering Excellence
1. Every merge to master makes us better
This principle reflects our commitment to high-quality standards. We hold customer experience above everything else and dedicate due diligence to considering what that might mean in terms of quality.
- Measure Quality: Teams should define what’s important to measure and create a baseline for continuous improvement.
- Act-On Quality: Every feature delivered should improve the overall quality of our codebase — and if not, we should understand and defend the reasoning behind it.
- Champion Quality: Act as an owner and hold the bar high for all team members. Data engineers are not the only ones writing code!
2. Design for the future
At Vista, our teams design products with the utmost practical utility in mind. We encourage our teams to think ahead and develop the most future-proof solutions co-operatively, ensuring long-lasting value instead of short-term shortcuts. Considering alternative solutions and defending decisions based on data have become core to this mindset.
- Considering long-term utility over short-term optimizations
- Employing data-driven optionality
- Reducing support costs makes more time for innovation
3. Security and data privacy are first-class priorities
We encourage voicing out openly and honestly about security concerns across all levels to ensure that the product and data remain protected from all directions. See something? Say something! Everyone is willing and able to help.
- Initiating and testing intricate security measures with maximum diligence
- Considering DNA best practices as a non-negotiable doctrine
- Security is taken up as a shared team responsibility
Team culture and values at Vista DnA
When you have 50 engineers worldwide working across 30 data product teams, things become complicated. However, the engineering excellence principles have helped us shape a culture-value system within our organization, enabling us to stick together in a global work environment. When we begin to digress from these values, we always ask why we’re doing that — and if there are no good answers — we act upon it promptly and hold each other accountable.
We cannot emphasize this enough, but the quality is a team effort.
Working as a team, not an operational silo
Teams at Vista are highly communicative and take a deep dive into technical topics when devising solutions, all while aligning operations with the engineering excellence principles. It is especially helpful in a remote-first environment.
All members of data product teams are jointly accountable for engineering excellence (not just the data engineers!). Through constructive discourses, teams evaluate the short-term and long-term trade-offs.
We design our solutions to minimize technical debt and prioritize work that helps reduce operational support costs so that we can spend more time innovating.
Balancing feature development and technical improvements is difficult. While short-term optimizations gratify the users, focusing on utility helps keep the solution defensible in the long run. This approach ensures that refinement doesn’t come at the cost of innovation.
Improvement as a mindset
Teams conduct constructive debates when prioritizing backlogs and assessing progress, which has now become a shared value system at Vista DnA, helping drive product quality as a matter of priority. Teams are encouraged to share their knowledge in public forums, such as our Slack channels and recurring tech talks. Both successes and failures are deemed essential for improvement.
Improving product quality ensures confidence in our data and helps drive data product adoption and data literacy across the organization at scale.
Team up for a cultural fit
Our journey to engineering excellence has only begun. We haven’t perfected the process yet. However, we’ve had some great results from this cultural change through quality measurement, inspection, and continuous improvement.
We celebrate quality and reliability! Intrinsic motivation inspires everyone to offer solutions and put in their best efforts. We hope to achieve this for the teams through patient and continuous communication so that we can build upon individual strengths to get a greater collective outcome. When you invest your ideas in a product, you tend to build a sense of ownership and feel every win as a personal victory. This philosophy has been instrumental in building a culture of teamwork.
This means that every member works with the same goals and values for our teams, giving rise to coherence in the team spirit. When there is an environment of resonance in a team, the best ideas come out.
With open dialogue and culture, we’re also able to bring this change faster through regular async collaboration between our distributed teams.
Want to be a part of our engineering excellence story? Check out open positions at Vista Data and Analytics.