Data Engineering
From lakehouse builds on Azure Databricks to automated Snowflake and AWS pipelines, we weave in Dynatrace observability to deliver real-time, AI-ready data.
- + Unified Lakehouse Engineering
- + Insight-Driven Analytics
- + Observability
- + Autonomous DataOps Pipelines
Data Lakehouse
Consolidate scattered warehouses into one governed
lakehouse, cutting storage costs, ending schema sprawl, and giving every AI or BI workload a single source of truth.
Performance tuning & cost-optimisation
Data Analytics
Turn raw data into metrics-ready models and push real-time insight back to the front line where decisions happen.
Observability
Monitor lineage, freshness, and SLAs end-to-end so issues surface before they hit production dashboards or models.
DataOps Pipelines
AI agents generate, test, and self-heal pipelines—reducing run-time effort by up to 40 % and delivering trusted data faster.
Client
Success Stories
A Retail Leader’s Transformation in the Age of Data
A major retail chain faced hurdles in using their extensive data effectively: low data literacy among staff, inefficient data processes, difficulty turning data into actionable insights, and the need for improved operations and customer experience.
See how we helped them
Implementing Data Analytics Platform for A Telecom Company
A prominent US telecom firm, The Customer, is engaged in the federal Lifeline Support Program. Specializing in prepaid cell phones and packages, they cater to low-income individuals, driven by their mission to offer widespread telecom services with a focus on serving the community.
See how we helped them
How A Modern Data Platform Can Increase Customer Usage
Striving for superior quality and customer experiences, the client aimed to outshine competitors by embracing a data-driven approach.