Data Engineering

Data Platform Modernization

Aging data platforms impose hidden costs: expensive hardware refreshes, skills scarcity for legacy technologies, and architectural constraints that block new use cases. We plan and execute migrations that move organizations to modern platforms without breaking the reports and models that business teams depend on.

60%

Infrastructure Cost Reduction

0

Analytical Downtime During Migration

5x

Query Performance Improvement

What We Deliver

Data Platform Modernization Services

Practical, production-ready work — not proofs of concept that never make it to real users.

Migration Assessment

Audit existing platform, catalog data assets, document dependencies, and produce a migration plan with risk rating for each workload.

Schema & Query Translation

Systematic conversion of platform-specific SQL dialects, stored procedures, and ETL jobs to modern equivalents.

Parallel Run Validation

Run old and new platforms in parallel to validate output equivalence before decommissioning the legacy system.

Team Enablement

Training and documentation so your data team can operate and extend the new platform independently after handover.

How We Engage

Common Engagements

01

Teradata to Snowflake

Migration of an on-premises Teradata data warehouse to Snowflake including SQL translation and pipeline rebuild.

02

Hadoop Sunset

Migration of Hadoop HDFS and Hive workloads to a cloud lakehouse on Databricks or BigQuery.

03

Legacy ETL Modernization

Replacement of Informatica or SSIS ETL jobs with modern dbt transformations and cloud-native connectors.

04

Consolidation Migration

Consolidate data scattered across multiple legacy platforms into a single governed data warehouse.

Why InnovTen

What You Can Count On

  • Structured parallel run phase catches discrepancies before users are affected
  • Migration sequenced so business-critical workloads move last with maximum validation
  • Elimination of legacy licensing and hardware support costs
  • Modern platform unlocks use cases like ML feature stores and real-time analytics
  • Reduced operational burden on data engineering teams from platform maintenance

Technologies We Use

Snowflake Databricks BigQuery Redshift dbt Fivetran Airbyte Terraform Python

Ready to Get Started?

Tell us about your project and we'll put together a practical path forward.

Talk to Our Team