Featured List
The data platform modernization consulting experts listed here are selected for their ability to fix what quietly breaks in legacy data systems – inconsistent outputs, slow pipelines, and governance gaps. We focused on practitioners who redesign data flows, restore reliability, and prepare platforms for analytics and AI without disrupting core operations.
Igor Omelianchuk CEO & Cloud Migration / Data Modernization Consultant
Legacy data modernization, delivery model optimization, cloud data migration, data architecture redesign, ETL/ELT pipelines, data integration, governance & compliance
15+
Igor Omelianchuk helps companies when their legacy data systems stop being reliable but cannot be replaced outright. He works with organizations where fragmented data, unclear data ownership, inconsistent outputs, slow reporting, and compliance risks begin to affect decisions. The focus of a data modernization consultant is to rebuild data flows, stabilize architecture, enable scalable pipelines, and move to the cloud where it makes sense. Igor has worked on over 30 projects with a consistent approach: modernize without breaking what the business still relies on.
Andrew Lychuk Legacy Modernization Expert, Technology Executive
Data architecture strategy, cloud migration planning, multi-cloud systems, data platform transformation, integration architecture, delivery model optimization
18+
Andrew Lychuk approaches data platform modernization consulting from a system-wide perspective. He’s typically engaged when data modernization is tied to larger architectural change, not just pipelines but the surrounding systems. With over 18 years in modernization and digital transformation, he works where legacy data, infrastructure, and delivery models intersect. His role is to define what should move, what should stay, and how data flows evolve without creating new risks. The focus is consistent: modernization that produces measurable outcomes, not just cleaner architecture.
Michael Curry President of Data Modernization Business Unit
Cloud architecture, data platform governance, DevSecOps, AI/automation enablement, cost optimization, cross-functional delivery
30+
Recognized among leading voices in data transformation, he works where legacy data begins to limit growth. Thirty years in enterprise systems show in his approach – practical choices over conceptual models. He leads initiatives that connect data modernization, hybrid cloud, and AI into a single operating model. In practice, this means rebuilding data foundations so they scale, integrate, and stay compliant under pressure. His work in IT modernization consulting focuses on outcomes: usable data, stable platforms, measurable efficiency gains, and staying ahead in the competitive tech industry.
Scot Carlson Enterprise Transformation & AI Strategy Leader
Enterprise AI strategy, data platform modernization, operating model design, responsible AI governance, digital platform strategy
16+
Scot Carlson’s work begins where data and platforms stop keeping up with business needs. When data ecosystems become too complex to trust, he works at the point where AI ambition meets fragmented reality. Over 16 years, Scot Carlson has worked with companies like Deloitte, Samsung, WPP, and Publicis, and he has helped them improve their data systems. He has led transformations that connect data, platforms, and operating models into something usable. The result is not just modernization, but systems that support real decisions, scale across regions, and remain governed as complexity grows.
Christopher Etheridge Technology & Data Services Leader
Enterprise data platforms, AWS GovCloud, Databricks architecture, data warehousing, pipeline optimization, compliance frameworks (FedRAMP, CMMC, ITAR)
20+
Christopher Etheridge works with data systems that are too complex and slow down the company. Reporting lags, pipelines stretch for hours, and compliance adds friction – he solves these bottlenecks. He addresses these problems by rebuilding architectures, optimizing data flows, and moving critical workloads to cloud platforms designed for scale. His work combines technical depth with operational impact: pipelines that run in seconds, systems that stay compliant, and data that is ready for analytics and AI use.
Alina Baranou Chief Data Officer
Data strategy & governance, cloud analytics platforms, BI modernization, data quality management, AI-ready data, cost optimization
15
Alina Baranou is brought in when data exists across the business but cannot be used consistently. Dashboards differ. Decisions slow down. Alina focuses on aligning data strategy with modern architecture. She breaks silos, introduces cloud-based analytics, and enables AI-driven insights that hold under real conditions. Her work emphasizes control and scalability. Data becomes reliable, accessible, and aligned with business needs, allowing teams to move faster without questioning the numbers behind each decision.
Sebastian Frassia Digital Transformation Lead | Tech Lead (Cloud, AI & Data Platforms)
Data engineering, cloud-native architectures, distributed systems, real-time analytics, platform scalability, system reliability
10+
Sebastian Frassia works with cloud and data platforms and focuses on the operational side of modernization. This includes defining governance, aligning teams, and ensuring data flows remain consistent as platforms scale. His background in AI and automation adds another layer: systems are designed to support decisions, not just store data. He makes sure the engineering and business decisions are aligned with the data quality, cost control, and system reliability so the efforts to modernize the data systems produce results rather than just small improvements.
André Nix Senior Architect for Cloud Solutions
Cloud infrastructure (AWS/Azure), IaC (Terraform, CloudFormation), CI/CD pipelines, hybrid cloud, cost optimization, disaster recovery
14+
André Nix focuses on data platform modernization consulting where legacy infrastructure meets cloud scale. Systems migrate, but instability follows. He addresses this gap directly – implementing IaC, optimizing CI/CD, and introducing serverless approaches that improve both reliability and cost control. His work is measurable: faster recovery, lower spend, stronger system resilience. Data platforms become predictable, not reactive, even under increasing load.
Amer Raza CTO & Co-Founder | Senior Cloud & DevOps Architect
Multi-cloud architecture (AWS/Azure/GCP), MLOps/AIOps, LLM systems, DevSecOps, containerization (Kubernetes), AI infrastructure
20+
In data platform modernization consulting, Amer Raza focuses on systems moving from traditional cloud setups into AI-driven environments. This shift introduces new pressure – latency, cost, model reliability. He addresses it directly, combining deep infrastructure experience with hands-on AI systems engineering. His background in multi-cloud, IaC, and DevSecOps supports platforms that scale without losing control. The outcome is consistent: production-ready systems that teams can operate, not just deploy.
Evans Tinga Cloud Migration Expert & Specialist Solutions Architect, AWS
Cloud migration (AWS), enterprise architecture, system integration, digital platforms, AI-driven development workflows, scalable infrastructure
13+
Sixteen years in enterprise transformation show in how Evans Tinga approaches cloud and data systems: structured, outcome-driven, grounded in real delivery. From large-scale migrations to payment platforms and transport systems, his work focuses on reliability under pressure. More recently, he has extended this into AI-driven development, shaping how systems move from architecture to working software without losing control.
Yetish Narayana Technology Leader – Cloud Migrations & Application Modernization
Multi-cloud (AWS/GCP/Azure), AI/ML data platforms, microservices, CI/CD pipelines, performance optimization, cloud governance
20+
In environments where data platforms grow faster than they are structured, Yetish Narayana focuses on restoring balance. His background spans multi-cloud transformations and analytics systems under real load. He addresses performance issues, inefficient resource use, and architectural drift by redesigning how data systems are deployed and scaled. The emphasis is not speed alone, but systems that remain stable as demand increases and complexity builds.
Strong data modernization consulting experts explain messy realities such as broken pipelines, conflicting reports, and unclear ownership. Posts, talks, webinars, short breakdowns. You want to see how they think when data is inconsistent and decisions depend on it.
Good consultants don’t start with “We migrated everything.” They explain what stayed, what changed, and why. Real experience shows up in constraints: legacy schemas, partial integrations, and data loss risks. That’s where data modernization consulting becomes real work.
Modernization fails quietly when data cannot be trusted. Look for consultants who have dealt with mismatched metrics, delayed pipelines, and reconciliation gaps. Not just dashboards but the underlying data. They should explain how trust was restored, step by step.
Data modernization often runs into regulation. GDPR, HIPAA, internal controls. Strong consultants describe how data flows were audited, secured, and monitored. Not just policies but implementation. What changed in pipelines, access, storage.
Most issues appear later: pipelines drift, costs grow, data duplicates, etc. Experienced consultants stay involved beyond delivery – monitoring, tuning, and correcting. If they only describe the “before and after,” something is missing.
Tools change. Data problems don’t. The right consultants explain trade-offs: batch vs. real-time, centralization vs. distribution, and speed vs. control. They align architecture with how your business actually uses data. That’s the difference between working systems and constant fixes.
Legacy Software Modernization