Data teams are critical for driving smarter business decisions. So, how do they do it?
According to Katie Balcewicz, a data engineering manager at direct mail software provider Lob, the key is to have the right tools and processes in place. For instance, she and her peers on the company’s “small but mighty” data team lean on various processes, such as the Extract > Transform > Load pattern framework, while ensuring stakeholders have access to the data they use to drive decision-making.
“Empowering stakeholders to answer their own questions, no matter their technical background, is our top priority,” Balcewicz said.
Meanwhile, at the Federal Reserve Bank of Boston, Principal Product Manager Semani Silva and her peers on the product fraud mitigation team help tackle real-life problems for financial institutions, relying on various tools, including AI, to make insights more actionable.
“Anything we provide that helps a financial institution stop a customer from getting scammed or defrauded is a win,” Semani said.
Semani and her teammates actively work to break down organizational silos, collaborating with teams such as pricing, operations and product design to keep everyone in sync. This creates an environment that facilitates better decisions — and protects more people from financial harm.
Read on to see what Balcewicz, Semani and leaders from DoubleDown Interactive LLC and Analytics8 had to say about what it’s like to work on their team, the tools and processes their team leans on every day, and how their team partners with stakeholders to turn data into action.
As part of the Central Bank of the United States, Federal Reserve Bank of Boston strives to promote sound growth and financial stability in New England and the nation by conducting economic research, participating in monetary policy-making, supervising certain financial institutions and more.
What’s it like to work on the data and analytics team at the Federal Reserve Bank of Boston?
I’ve spent 13 years at the Federal Reserve on multiple teams. The organization is constantly changing, but the Fed is consistent about its investment in people and the passion our teams have for the Federal Reserve’s mission to promote economic growth and stability in New England and the nation.
As part of the FedNow Service’s product fraud mitigation team, I work primarily on customer-facing products. We help tackle real-life problems for financial institutions. It’s exciting to design solutions for our customers, and it’s even more satisfying to see those products protect their downstream customers. Anything we provide that helps a financial institution stop a customer from getting scammed or defrauded is a win.
What tools, systems or processes help your team deliver useful insights?
Knowing the latest technology and techniques is critical. It helps that data is quickly becoming less complex and more accessible. Instead of relying on complicated code and inflexible dashboards to find and interpret data, users can get what they need by asking in natural, conversational language. AI is fundamentally changing how we interact with data and deliver insights, and I know things will continue to evolve. We are lucky to be in an organization that’s so focused on training us how to use the latest tools to best reach our customers.
“AI is fundamentally changing how we interact with data and deliver insights, and I know things will continue to evolve.”
My team is constantly exploring different ways to support customers and colleagues with the data available to us. That includes using AI to make insights more actionable. But data work is never static. You must consistently iterate and respond to quick demands. We build in a way that lets us do that.
The Federal Reserve emphasizes continuous training and engagement. I’ve been on different data teams within the Federal Reserve, and I’ve never been denied training that I’ve requested. They really invest in people and in improving our skills.
How does your team partner with stakeholders to turn data into action?
We never build products in a vacuum. We set up systems that can work seamlessly with our customers’ systems and give useful insights.This usually isn’t just data analysis. Our team partners closely with data scientists, Agile Release Train teams, and, most importantly, our customers. We have ongoing conversations with stakeholders to better understand their needs, not just about the data they want, but about what products can help them integrate it quickly.
Internally, we work to break down organizational silos and partner with other teams. Our leadership is focused on data-driven decision-making. From pricing to operations and product design, our organization relies heavily on our data teams to help determine its direction. The combination of mission-driven work, continuous learning opportunities and collaborative problem-solving creates an environment where data teams can drive smarter decisions that protect real people from financial harm.
With its nationwide Print Delivery Network and end-to-end automated platform, Lob enables businesses to build personalized direct mail programs at scale.
What’s it like to work on the data and analytics team at Lob?
Here at Lob, we compare our data platform to a garden — an organic, evolving ecosystem that changes over time. We on the data team are the gardeners; we plant the seeds, water the sprouts and prune religiously. All our colleagues are invited to explore the garden and search for the most vibrant blooms.
Lob’s data team is small but mighty. With just four people on the team today, we’ve been able to transform the Lob data ecosystem. Although we all have our specialties, everyone gets the chance to become familiar with the entire pipeline.
On this team, we have a tri-fold responsibility: We faithfully replicate data from product engineering teams, surface data to our customers in the Lob UI and empower internal stakeholders via access to dashboards and the warehouse. Being between worlds gives us a unique perspective and a unique ability to translate their concerns.
“Being between worlds gives us a unique perspective and a unique ability to translate their concerns.”
What tools, systems or processes help your team deliver useful insights?
On the Lob data team, we follow the Extract > Transform > Load pattern and use a variety of tools from the modern data stack.
Extract: We ingest data from third-party sources like USPS and other logistics providers. We replicate data from internal application Postgres databases using CDC and AWS DMS.
Load: All extracted data sources are deduped, reconciled and stored in Iceberg tables.
Transform: Using dbt Core and Prefect, we orchestrate incremental refreshes of core and domain-specific data models.
Ultimately, this data is surfaced to internal stakeholders via Omni, a BI tool that offers a conversational interface powered by the context of our curated semantic layer. Omni connects directly to dbt, so we’re able to maintain close alignment with our data lineage.
How does your team partner with stakeholders to turn data into action?
The data and analytics engineers on the core data team focus on building out clean, curated and performant core data models so that we can enable stakeholders across the entire company to discover domain-specific insights. We each develop a focus on one or two domains, which helps us answer specialized questions.
Data analysts, who sit directly within business teams, use this data to build dashboards, insights and predictive models for their teams. They can also contribute to the shared dbt project and build custom data models to power their own use cases.
All Lob employees — from the operations team to customer success to the C-suite — have access to Omni and our shared dashboards. We’ve all grown fond of our data agent, Lobbie, where we ask questions about everything from logistics bottlenecks to customer trends to financial projections. Empowering stakeholders to answer their own questions, no matter their technical background, is our top priority.
DoubleDown Interactive LLC is the global gaming company behind several social casino games, including DoubleDown Casino and DoubleDown Classic Slots.
What’s it like to work on the data and analytics team at DoubleDown Interactive LLC?
Working with data at DDI is a great experience because there are continuous new projects to work on. As each new third party is brought into partnership, our team has a new puzzle to figure out and new obstacles to overcome. It keeps things interesting and avoids the staleness that other areas of study eventually get. Our team works closely to tackle these challenges together and is very tightly knit so that we can collectively solve the technical tasks that come our way. This also means that when one member is facing challenges, the others are able to jump right in and help without worrying about siloed knowledge.
“As each new third party is brought into partnership, our team has a new puzzle to figure out and new obstacles to overcome.”
What tools, systems or processes help your team deliver useful insights?
On our team, we’re big fans of Amazon’s infrastructure, particularly their Redshift database, which we use to store and access big data without being held back by storage and access speed limits. We also love working with and contributing back to open-source software where appropriate. One such product is Apache Airflow, which we use to coordinate all of our Extract > Transform > Load processes and keep data continuously flowing to our stakeholders reliably. Another open-source tool we use is Redash, which allows non-tech experts to still jump in and use data prepared by our engineers to drive their own insights and team goals.
How does your team partner with stakeholders to turn data into action?
Our stakeholders drive the core of our work on this team, and every improvement we make to the data or infrastructure is ultimately driving toward ‘Does this change help our other teams get the data they need?’ The process starts with just being very present in the day to day of what our stakeholders are working on so we can fully understand what’s important to them, so when they come to us asking for help, we already have a level of understanding. We also make sure to sit down with our team’s partners and really understand the underlying goals of their needs so that when we do deliver to them, we can make sure to get it right as early as possible and deliver value right away with less need for iteration. Ultimately, when iteration is needed, we keep continuous communication open through the iterations to ensure that each change is delivering more value each time and is not a setback.
Analytics8 is a data analytics consultancy that offers services such as data governance, cloud architecture optimization and generative AI implementation.
What’s it like to work on the data and analytics team at Analytics8?
Sitting at the intersection of the technology and human sides of data and AI is incredibly rewarding. Every project presents a unique opportunity to transform data into meaningful insights that drive better decision-making for our clients.
One of my favorite parts of working at Analytics8 is the variety of clients we serve and the technological solutions we deliver. Because we support the entire data lifecycle, every engagement is different. We get to design solutions that fit their technology ecosystem, solve today’s challenges and create a foundation for future growth.
I work closely with client stakeholders across many business functions to understand their goals, identify areas for improvement and develop solutions that turn data into measurable business value. The industry never stands still, and neither do we. Through continuous learning and knowledge-sharing, we stay current with emerging technologies and deliver the best possible outcomes for our clients.
“Through continuous learning and knowledge-sharing, we stay current with emerging technologies and deliver the best possible outcomes for our clients.”
What tools, systems or processes help your team deliver useful insights?
We work across data and analytics platforms like Databricks, dbt, ThoughtSpot, Sigma, Snowflake and Coginiti. But valuable insights require more than technology — they depend on strong processes, governance, validation and stakeholder engagement for trustworthy and actionable results.
That structure comes from our Analytics8 Delivery Methodology, which aligns every engagement to business outcomes. For scenarios that slow data teams down, Accelr8 is our accelerator that brings AI-powered automation to expedite delivery while maintaining quality and consistency.
On a current project, I’m performing customer segmentation using membership data enriched with third-party demographic, financial and lifestyle information, developing personas that give a deeper understanding of their membership base. Within that engagement, Snowflake CoWork and CoCo have been particularly valuable, helping with validation, uncovering additional insights and translating between SQL and Python. One of my favorite use cases during analytics intake: Rapid visualizations let me quickly assess requests, engage business stakeholders and determine whether development in a dedicated BI tool is warranted.
How does your team partner with stakeholders to turn data into action?
Every successful data initiative is built on a strong partnership. One of the things I enjoy about consulting is working on the people side of data. Rather than simply delivering reports, I help uncover the right questions and translate stakeholder needs into solutions that drive meaningful business outcomes.
While development is vital to any project, we view discovery sessions, requirements gathering, demonstrations, training/enablement and feedback reviews as critical to success. That collaboration keeps our stakeholders engaged and confident in the solutions we deliver.
And our role doesn’t end at delivery. We stay engaged to help our clients interpret results, identify new opportunities and prioritize actions that support business objectives. Through that level of partnership, our clients move beyond reporting and turn their data ambition into measurable business value.
