Data Engineering
Build a Foundation for Scalable, Trusted, and Intelligent Data
Modern cloud-native data platforms, engineered for analytics, AI, and enterprise scale
Enterprise data is only as powerful as the platform that moves, governs, and serves it. Techknomatic helps organizations modernize fragmented data ecosystems into unified, cloud-native foundations built on Azure, AWS, GCP, Snowflake, and Databricks. From high-throughput ETL/ELT pipelines and real-time streaming to lakehouse architectures and governance frameworks, we deliver data engineering that is reliable, observable, and audit-ready.
Our solutions combine deep platform expertise with reusable accelerators, connectors, transformation frameworks, and quality libraries, that compress delivery timelines and reduce risk. The result is a scalable data foundation that powers BI, advanced analytics, and AI/ML initiatives across the enterprise.
What We Offer
ETL/ELT Pipelines & Automation
Reliable, scalable pipelines built with Talend, Azure Data Factory, Informatica, dbt, and Python.
Cloud & Platform Setup
Modern data platforms on Azure Synapse, Snowflake, Databricks, and Redshift, engineered to scale.
Salesforce Cloud Integration
Seamless Salesforce data integration to power a unified enterprise customer view.
Metadata & Master Data Management
Trusted data assets through MDM, metadata governance, and enterprise data catalogs.
Real-Time & IoT Engineering
Streaming pipelines on Kafka, Event Hubs, and Spark Streaming for low-latency insights.
Data Quality & Governance
Automated quality checks, cleansing routines, and governance frameworks for trusted data.
Tools & Technology
A platform-agnostic stack, we choose the right tool for your architecture, not the other way around.
Our Approach
A proven 5-step delivery framework that takes you from assessment to optimized operations.
Assess
We map your data sources, identify gaps, and define what needs fixing first.
Architect
We design your end-to-end data flow and align on expectations before we build.
Build & Automate
Develop pipelines with CI/CD, parameterized configurations, and automated quality checks at every stage.
Test & Monitor
Run data-quality assertions, lineage validation, and load tests. Stand up alerting and SLA dashboards.
Operate & Optimize
Hand off to managed operations or upskill your team. Continuously tune cost and performance.
Use Cases
Three high-impact data engineering programs for modern, trusted, and real-time enterprise data platforms.
Data Platform Modernization & Cloud Lakehouse Engineering
Re-architect legacy data ecosystems into a scalable cloud-native foundation.
Migrate fragmented ETL workflows and legacy warehouses into a governed lakehouse built on modern cloud platforms and orchestration tools. Design Bronze–Silver–Gold data layers that unify batch and streaming data, standardize transformations, and serve analytics, AI, and BI workloads from a single trusted backbone.
Industries
BFSI · Insurance · Manufacturing · Retail · Telecom
Impact
Significantly simplified data landscape · Remarkably faster analytics delivery · Stronger foundation for AI and advanced reporting
Real-Time Operational Intelligence & Streaming Data Platforms
Transform enterprise operational data into actionable, real-time business intelligence.
Build event-driven analytics platforms using streaming, CDC, and dimensional modeling to continuously process operational signals from ERP, CRM, IoT, ITSM, and transactional systems. Consolidate these feeds into low-latency operational views that empower teams to monitor performance, detect anomalies, and act on insights as they unfold.
Industries
Oil & Gas · Logistics · ITSM · Telecom · Supply Chain
Impact
Substantially improved decision speed · Enhanced visibility into live operations · Stronger responsiveness to business events
Data Quality, Reconciliation & End‑to‑End Observability Analytics
Engineer trust into every stage of the data lifecycle.
Embed automated validation, reconciliation, schema-drift detection, lineage tracking, and SLA monitoring directly into data pipelines and transformation layers. Leverage cloud-native data platforms and observability tooling to surface data issues early, protect critical reports, and strengthen compliance with internal and regulatory standards.
Industries
BFSI · Insurance · Healthcare · Regulated Organizations
Impact
Considerably higher data reliability · Reduced reporting and reconciliation risk · Enhanced confidence in regulatory and management reporting