Services

At Opus, we engineer future-ready solutions that help banks, fintechs, and PayFacs modernize, scale, and stay compliant in a dynamic business landscape.

Whether you’re grappling with legacy debt, building new digital rails, or launching next-gen services, our engineering capabilities are designed to accelerate your business outcomes — securely and at scale.

Consulting

Engineering

Data and AI

Industries

At Opus, we bring deep domain expertise and an AI-augmented toolset to enable banks, payment providers, and fintechs accelerate their modernization, innovation, and enterprise AI journeys.

Whether you grapple with evolving regulations, build new rails, or launch next-gen services, we enable you to turn engineering into business advantage securely and at scale.

Industries

Insights

Ideas and insights from the minds of leaders, practitioners, technologists, and domain specialists shaping what’s next in banking, fintech, and payments.
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Turning data silos into trusted decision intelligence

Financial institutions are under increasing pressure to deliver seamless payment experiences, scale digital banking capabilities, and launch new products faster while meeting stringent risk and regulatory expectations. Legacy platforms and fragmented data landscapes limit real-time visibility across transactions, customers, and channels. Fragmented infrastructure slows innovation, weakens risk monitoring and compliance reporting, and prevents banks from fully leveraging data for real-time insights, operational efficiency, and sustainable competitive advantage

Our data engineering services help you build trusted, low-latency foundations that transform fragmented data into actionable intelligence. We combine Payments and Banking domain expertise with AI-augmented engineering and proven accelerators to map your Data Universe, modernize platforms, and embed governance and observability.

Our services include:

  • Data strategy Cloud
  • Cloud data platform
  • Data governance & trust
  • Data observability & health
  • Data catalogs & discovery
  • Data quality engineering

Our data engineering services

Data strategy

Map and organize your domains for clarity and control. We conduct comprehensive information discovery and design logical domains aligned to your Payments and Banking operations. Our multi-layer foundations transform raw enterprise data into harmonized, business-ready insights, creating a unified Data Universe with clear priorities and accountability for faster, trusted decisions.

Cloud data platform

Migrate to cloud-native infrastructure with confidence and speed. Our architects assess your current landscape and design modern lakehouse or mesh architectures matched to your needs. Intelligent migrations, powered by AI-led schema mapping and automated validation, seamlessly move data from legacy systems to scalable cloud platforms, supporting both real-time and batch workloads with zero downtime.

Data governance & trust

Build ownership, policies, and controls that inspire confidence in your data. We establish domain-led frameworks that align accountability to your logical data domains, embedding privacy and security policies directly into platforms. Role-based access, dynamic masking, and end-to-end lineage tracking make your ecosystem auditable, compliant, and trusted.

Data observability & health

Monitor data health continuously and resolve issues before they impact business. Our holistic monitoring spans across the ingestion, transformation, and consumption layers, while AI-driven anomaly detection surfaces issues proactively. Real-time alerts on timeliness, schema changes, and distribution drift ensure your data remains reliable and decision-ready.

Data catalogs & discovery

Unlock data consumption through intelligent search and business context. We automate metadata harvesting across your platforms and enable graph-based discovery, connecting datasets to teams and use cases. Enriched with definitions, quality scores, and ownership details, your catalog drives self-service access and broad team adoption.

Data quality engineering

Embed automated guardrails that ensure every dataset meets your business and technical standards before use. We create domain-specific quality rules powered by AI, automating validation at every transformation step with closed-loop remediation. The process ensures that quality becomes a built-in, proactive capability, protecting your critical decisions from bad data.

The Opus playbook for data engineering excellence

01

Assess & define

We begin by performing data inventory and profiling to understand your current state, then map end-to-end lineage to identify all dependencies. By classifying data for compliance and defining the "R Strategy" for each asset, we enhance downstream consumption, establishing a clear foundation for modernization.

02

Plan & design

Next, we architect cloud schemas and design domain-based Logical Data Models across Producer and Consumer data products (silver and gold layers). We establish ingestion patterns, orchestration logic, and a detailed Source-to-Target mapping framework. Data catalogs, including ERDs, metadata, and data flow diagrams, ensure transparency and alignment across your enterprise.

03

Execute & migrate

With the blueprint in place, we execute historical backfills and configure Change Data Capture (CDC) to ensure real-time synchronization during the migration. Our AI accelerators refactor legacy procedures and upgrade logic. Automated DQMS scripts act as preventive and detective controls on ingestion pipelines. We build data contracts to ensure transparent governance and compliance, while updating catalogs based on schema changes.

04

Optimize & scale

Once live, we perform query tuning and optimize warehouse compute to reduce latency and costs. We implement data monitoring and controls, then build data as a service (DaaS), leveraging graph-based cataloging to drive consumption. Data Mesh enables decentralized ownership through domain-native data products, while AI/ML feature stores feed downstream models and automated decision engines for consumer applications.

Our proven accelerators for data engineering success

AI-powered converter for code migration

Translates legacy SQL and stored procedures into modern cloud-native code, slashing migration timelines and manual effort.

AI DQMS generator for quality automation

Creates domain-specific quality rules and automated safety nets that ensure compliance and prevent downstream issues.

AI schema mapper for field mapping

Automates source-to-target field mapping to eliminate design errors and accelerate platform transitions.

AI triage agent for incident response

Monitors pipelines proactively to slash MTTR and resolve data incidents before they impact business.

Payments data models for transaction standardization

Pre-configured pipelines that standardize raw transaction data for instant analytics and compliance use.

Success stories

Decommissioning legacy payment gateway through merchant data migration

A multinational Fortune 500 fintech and payments company needed to decommission its payment gateway while managing merchant data for approximately 140,000 small and medium-sized businesses and ensuring alignment with corporate strategy. We conducted a detailed analysis, proposed Google Data Fusion as the ETL tool, created comprehensive data dictionary documentation for 500+ tables, and developed custom API layers supporting 24 versions of client interfaces.

>$5M/ year saved on maintenance
140k merchants migrated
Zero downtime during migration
Wisconsin, US
USA
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Cloud-native data platform unifies consortium banking

A consortium of over 400 North American banks partnered with Opus to consolidate fragmented systems and streamline real-time analytics. Opus partnered with the consortium to integrate SaaS applications, enable automated data pipelines for two major entities, and optimize the platform to scale across up to 20 subsidiaries annually.

60% reduction in SaaS integration effort
1.5x boost in data availability across subsidiaries
Real-time analytics operationalized for all member banks
Washington, United States
USA
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Interactive fraud analytics dashboards for leading American fintech

A leading American fintech firm providing integrated payment processing and fintech solutions to banks and credit unions struggled with delayed operational reports, a lack of actionable insights, and an inability to mitigate customer risk exposure. Opus partnered with them to drive end-to-end design and deployment of a fraud data mart. The team conducted data profiling, built Tableau-based interactive dashboards, managed data pipelines and ingestion, and implemented data partitions and indexes for ETL jobs across fraud data and scheduled reports.

Streamlined Operational Reporting Processes
Reduced False Positive Alerts
Reduced False Transactions Data
US
USA
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Turn siloed financial data into trusted intelligence that powers faster insights and decisions

Schedule a consultation with our data and AI team today.

Frequently Asked Questions

About us

Opus is a trusted engineering partner to payment providers, banks and fintechs navigating change in a real-time, digital-first world.

Our promise is simple: Business Value Acceleration. Realization. Maximization.

We deliver on this promise through the Opus trifecta-a domain-native engineering skillset, a value-creation mindset, and an Al augmented toolset that drives business agility.

From MVP (Minimum Viable Product) to MPT (Maximum Possible Transformation), Opus turns engineering into business advantage.