When Data Shapes Futures: How Engineers Built a Foundation for Smarter Retirement Planning
Retirement isn’t just a phase, it’s a promise. For millions, it’s the reward for decades of work, a chance to travel, rest, or start anew. Yet, behind every 401(k) plan or pension lies a complex web of data: participant contributions, market performance, and regulatory rules. In 2024, the U.S. retirement industry managed over $40 trillion in assets, according to the plan advisor. A single misstep, outdated records, or a delayed report can erode trust or cost millions. Financial firms, from advisors to recordkeepers, rely on precise, accessible data to guide clients toward secure futures.
Firms juggle vast datasets of transaction logs, compliance filings, and client profiles across sprawling operations. About 70% of financial institutions are falling behind on payments, leading to delays in reporting and analytics. Manual processes, once manageable, now choke under the weight of live demands. Advisors need instant insights to adjust plans; regulators demand flawless audits. Meanwhile, clients expect transparency, like checking a bank app. Older systems buckle under these pressures, leaving teams scrambling to reconcile errors. The industry doesn’t just need better tools, it needs a new way to think about data itself.
Picture a retiree waiting for a plan update that’s delayed because data’s stuck in several databases. Or an advisor unable to benchmark a client’s portfolio, losing their confidence. The stakes touch lives, families planning college funds, and small businesses offering employee benefits. Firms must deliver insights faster, cleaner, and with absolute trust.
Santosh Durgam is a Manager of Software Engineering. Based in Chicago and leading a global team across Mumbai and Toronto, he is an integral part of the effort to make data the basis of retirement planning. Among his accomplishments, one stands out: designing and implementing a centralized data lake for his employer firm’s retirement business. “Data isn’t just code. It’s the clarity someone needs to plan their life,” states Santosh.
His solution was a retirement data lake, a unified architecture to consolidate structured and unstructured data, from contributions to market trends. Built on modern ELT pipelines, it ingests data at scale, ensuring a single source of facts. Santosh used cloud-native tools, like AWS Redshift and Snowflake, to handle massive volumes without lag. “It’s about making data work as fast as people need it,” he says. This innovation supports live analytics, letting advisors pull benchmarks instantly or auditors verify compliance on demand. He added governance layers, lineage tracking, validation checks to catch errors before they spread, and a shield for accuracy.
Legacy systems weren’t built for integration; some lacked APIs entirely. Santosh mapped every data flow, designing custom connectors to bridge gaps. He stress-tested the lake under peak loads, think tax season, when millions of records flood in, refining it to stay stable. “You don’t build for today’s data,” he says. “You build for tomorrow’s growth.”
The data lake slashed time-to-insight, cutting report generation from days to hours. Data silos vanished, with teams accessing clean, consistent records instantly. “It’s like turning on a light,” Santosh notes. His employer firm’s analytics products, like peer benchmarking for advisors, grew sharper, driving client retention. Quantifiably, it saved millions by streamlining operations, no more redundant queries or manual fixes. Compliance risks dropped, with audits now a matter of clicks, not weeks.
In financial services, where trust hinges on precision, Santosh’s data lake set a new standard. Most firms still lean on fragmented systems; his unified approach showed data could be a strategic asset, not a liability. Industry peers took notice as Santosh fields calls from firms eyeing similar architectures.
With PwC projecting $5 trillion in potential retirement asset capture, data bottlenecks threaten progress. Santosh’s lake offers a blueprint: centralized, governed, and fast. Healthcare firms could adapt it for patient records; insurers for claims processing. “Data’s universal,” Santosh says. “The principles hold.” His work aligns with his employer firm’s push for transparency, earning praise in internal reviews as “foundational.” Advisors using the lake’s insights close deals faster; participants see clearer paths to retirement.
The metrics tell a story: faster insights, zero silos, millions saved. But the heart is human. It’s the advisor who reassures a client with real-time data. The retiree who checks their plan without worry. The engineer who builds boldly, knowing the data is solid. “I think about them,” Santosh says. “One clean dataset can mean one less sleepless night.” In an industry where futures hang on trust, his data lake isn’t just a system; it’s a legacy, ensuring the numbers add up to lives well-lived.
