Managed Data Services

Building the platform is the beginning. We keep it performing to create long-term value.

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Your data platform should scale outcomes, not maintenance effort.

Organizations often invest heavily in modern data platforms, only to find that sustaining performance becomes increasingly difficult once implementation is complete. Pipelines require ongoing attention, cloud costs rise, technical debt accumulates, and lean internal teams spend more time resolving issues than delivering new capabilities. 

We solve this by providing managed data services through our flexible COE POD model.  Combining data engineering, analytics, platform, and governance expertise in a scalable operating structure, we help you create a reliable, continuously optimized data ecosystem that controls costs, adapts to changing business needs, and allows your team to focus on innovation rather than maintenance.

How we
make it possible

How we make it possible

We organize managed service delivery through a COE POD model, with dedicated, self-sufficient teams built around your specific data domains and business needs. Each POD is anchored by a US-based lead who manages client relationships and quality, supported by nearshore and offshore practitioners with deep platform specialization. 

 

 

Here’s how our engagement model works.
  • Data Solution Architect (US-based)
  • Senior Data Engineers
  • Data Engineers
  • QA Engineers
  • ETL Developers
  • Cloud Engineers
  • Data Science Lead / SME (US-based)
  • Data Scientists
  • Data Analysts
  • Machine Learning Engineers
    • One rate across all POD resources
    • No per-role negotiation
    • No billing complexity

 

    • PODs and roles added based on evolving needs
    • No fixed CAPEX commitments

 

    • Centralized program management
    • Consistent quality, testing, and delivery governance across every engagement

 

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Multiplying outcomes for your business

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Managed Data Engineering

Ensure continuous improvement through ongoing data pipeline development, maintenance, and optimization, anchored in SLA-based delivery with proactive monitoring and incident management.

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BI and Analytics as Managed Services

Keep your analytics environment up-to-date through ongoing BI estate management, including report maintenance, performance tuning, platform upgrades, user support, and usage analytics. 

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Cloud Platform Operations and Optimization

Monitor platform health, manage cloud costs, right-size compute, and implement FinOps controls across Snowflake and Databricks. Keep infrastructure costs predictable and performance consistent.

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DataOps and Automation

Implement CI/CD pipelines, automated data quality checks, observability frameworks, and DataOps workflows. Reduce manual intervention, improve release reliability, and accelerate delivery cycles.

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Analytics COE and Team Enablement

Set up and operationalize an internal Analytics Centre of Excellence with governance models, tool standards, data product ownership, and analyst upskilling programs. Build the capability to reduce future dependency on external support.

Helping your leaders accelerate decisions

Once the platform is live, maintaining specialized expertise across modern data technologies can become costly and difficult to scale. Our COE POD model provides flexible access to certified Snowflake, Databricks, and dbt expertise without increasing permanent headcount.

CIO/CDO

Engineering teams can end up spending too much time managing incidents and maintaining platforms instead of building new capabilities. We provide embedded support that preserves institutional knowledge and keeps innovation moving forward.

Head of Data Engineering

Cloud and platform costs often grow without clear visibility or accountability. We apply FinOps-informed platform management with cost visibility dashboards, right-sizing recommendations, and active resource governance to improve transparency and keep spending predictable.

CFO

As analytics environments grow, report maintenance, performance issues, and support requests can overwhelm internal teams. We keep BI platforms optimized, current, and reliable without adding staffing overhead.

Head of Analytics and BI

Many data programs lose momentum after implementation as ownership shifts and operational support falls short. We provide a structured transition to steady-state operations that sustains performance and long-term value.

Program and Transformation Leaders

Impact tailored for your industry

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Financial Services

Provide managed platform operations and compliance monitoring support across risk, reporting, and finance data environments. Maintain audit readiness and SLA adherence on an ongoing basis.

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Asset & Wealth Management

Provide ongoing data engineering, reporting, and analytics support across investment management operations. Scale up during peak reporting periods without permanent headcount commitments.

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Travel & Hospitality

Sustain complex, multi-system data platforms across reservations, guest, marketing, and operational domains. Maintain SLA performance across high-volume transactional environments.

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Media & Entertainment

Maintain and evolve financial data warehouse and content analytics platforms post-implementation. Manage platform health, data quality, and reporting cadences across close cycles.

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Manufacturing & CPG

Manage procurement, supply chain, and operational analytics platforms by ensuring pipeline reliability and reporting accuracy as source systems and business requirements evolve.

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Life Sciences & Pharma

Sustain finance, clinical, and regulatory reporting platforms with ongoing data engineering and quality monitoring. Support periodic regulatory submissions and audit cycles.

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Results you can count on

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93%

Client retention rate

500+

Projects delivered

120+

Data professionals

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Delivery regions (US, India, and Latin America)

Long-Term Data Engineering Partnership with a Global Cruise Line Long-Term Data Engineering Partnership with a Global Cruise Line
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Long-Term Data Engineering Partnership with a Global Cruise Line

Travel and Hospitality - A leading global cruise line operator ($9.4Bn+ revenue)

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20+ engagements delivered

Coverage across engineering, analytics, marketing, and risk functions

Multi-year managed service partnership

Managed Data Engineering Services for a Large Retail Organization Managed Data Engineering Services for a Large Retail Organization
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Managed Data Engineering Services for a Large Retail Organization

Retail - A large US retail organization

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Dedicated COE POD established

Ongoing support for data governance, engineering, and Alation implementation

Services delivered across a large-scale retail data environment

Ongoing Analytics and Reporting Support for a Global Asset Manager Ongoing Analytics and Reporting Support for a Global Asset Manager
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Ongoing Analytics and Reporting Support for a Global Asset Manager

Asset Management - A global alternative investment firm ($4Bn+ revenue)

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Sustained data engineering and reporting support

Coverage across four separate engagement workstreams including GL tagging, P2P reporting, T&E analytics, and fund reporting

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outcome outcome

Why Data Platforms Degrade After Go-Live and How Managed Services Prevent It

outcome outcome

The COE POD Model: A Better Way to Scale Data Engineering Capacity

outcome outcome

Build vs. Buy vs. Partner: How to Think About Long-Term Data Platform Resourcing