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BRILLIQS

Data Engineering Services

Build scalable, reliable data pipelines that power analytics and AI

Build robust data pipelines to streamline collection, transformation, and storage across diverse sources. Enable high performance data infrastructure for AI driven insights and automation.

Automated ETL/ELT pipelines
Real-time & batch processing
Cloud-native architecture
Sources
Transform
Warehouse
Analytics

ChallengesWeSolve

These are the problems enterprises face every day — and exactly why they partner with Brilliqs.

01

Broken Data Pipelines Cause Silent Failures

Overnight pipeline failures go undetected. Teams discover stale dashboards hours later, eroding trust in analytics and delaying critical business decisions.

02

Manual ETL Scripts Waste Engineering Time

Data engineers spend 60% of their time maintaining fragile scripts, running manual imports, and debugging CSV parsing errors instead of building scalable infrastructure.

03

Data Silos Prevent a Unified View

Customer, financial, and operational data live in disconnected systems — CRM, ERP, spreadsheets — making it impossible to get a single source of truth.

WhatChangesAfterWeDeliver

99.9%

Pipeline Uptime SLA

Automated monitoring, self-healing retries, and real-time alerting ensure data pipelines run reliably around the clock.

60%

Reduction in Manual Data Work

Fully automated ETL/ELT pipelines replace manual scripts, freeing engineers to focus on high-value data products.

1

Unified Data Warehouse

All sources consolidated into a single, governed data warehouse — clean, deduplicated, and ready for analytics and AI.

KeyCapabilities

01

Data Pipeline Development

Design and build scalable pipelines to collect, process, and transform data efficiently

02

ETL & ELT Automation

Automate data extraction, transformation, and loading for faster and reliable workflows

03

Data Integration

Seamlessly connect multiple data sources into a unified and consistent system

04

Data Quality & Validation

Ensure accurate, clean, and consistent data with validation and monitoring processes

05

Scalable Data Architecture

Build cloud-based data systems that scale with growing business needs

06

Real-time Data Processing

Enable real-time data streaming and analytics for faster decision-making

OurApproach

A proven 4-phase methodology refined over 20+ years of enterprise delivery — designed for minimal risk and maximum impact.

1
1–2 Weeks

Discover & Assess

We audit your current systems, data landscape, and pain points to build a clear picture of where you are and where you need to be.

Deliverables

Current state audit report
Gap & risk analysis
Prioritized recommendations
2
2–3 Weeks

Design & Architect

We design the target architecture — selecting the right tools, cloud services, and patterns for your scale, budget, and compliance needs.

Deliverables

Architecture blueprint
Technology selection rationale
Implementation roadmap
3
4–8 Weeks

Build & Automate

We build production-grade solutions in 2-week sprints with automated testing, CI/CD, and stakeholder reviews at every milestone.

Deliverables

Production-ready solution
Automated CI/CD pipelines
Quality & monitoring framework
4
Ongoing

Deploy & Optimize

We deploy to production with full monitoring, optimize performance, and transfer knowledge to your team. We stay on for ongoing support.

Deliverables

Production deployment & cutover
Monitoring & alerting setup
Team training & documentation

Ready to Start?

Phase 1 is a free discovery call — no commitment, just a conversation about your challenges.

Book Free Discovery Call

TechnologiesWeUseforDataEngineering

We leverage the world's most robust data and AI frameworks to build scalable, future-proof platforms.

Apache Kafka
Apache Spark
Apache Airflow
dbt
Snowflake
Databricks
AWS Glue
Azure Data Factory
Apache Kafka
Apache Spark
Apache Airflow
dbt
Snowflake
Databricks
AWS Glue
Azure Data Factory
Apache Kafka
Apache Spark
Apache Airflow
dbt
Snowflake
Databricks
AWS Glue
Azure Data Factory
Apache Kafka
Apache Spark
Apache Airflow
dbt
Snowflake
Databricks
AWS Glue
Azure Data Factory
Google BigQuery
PostgreSQL
MySQL
Python
Scala
Docker
Kubernetes
Google BigQuery
PostgreSQL
MySQL
Python
Scala
Docker
Kubernetes
Google BigQuery
PostgreSQL
MySQL
Python
Scala
Docker
Kubernetes
Google BigQuery
PostgreSQL
MySQL
Python
Scala
Docker
Kubernetes

SampleEngagements

Real projects, real outcomes. Here's how we've delivered measurable impact across industries.

Challenge

A Pune-based automotive parts manufacturer operated 12+ disconnected data sources across MES, ERP, and IoT systems — causing 4-hour reporting delays and frequent data conflicts.

Our Solution

Deployed a real-time streaming pipeline using Apache Kafka and Spark, feeding a centralized Snowflake warehouse with automated dbt transformation models and Airflow orchestration.

Impact

Reporting latency reduced from 4 hours to 8 minutes. Production downtime decreased by 35%. Annual savings of ₹1.2Cr in operational efficiency.

Industry

Manufacturing

Challenge

A multi-hospital network needed to unify patient records from 40+ clinical systems while maintaining strict HIPAA compliance and sub-second query performance.

Our Solution

Architected a secure data lake on AWS S3 with Lake Formation access controls, automated PII encryption, comprehensive data lineage, and real-time quality validation rules.

Impact

Achieved 99.97% data accuracy across all hospital systems. Passed HIPAA audit with zero findings. Patient lookup time reduced from 12 seconds to 400ms.

Industry

Healthcare

Challenge

India's second-largest fleet operator processed GPS and sensor data from 5,000+ vehicles using manual spreadsheets — causing 24-hour delays in route optimization decisions.

Our Solution

Built an event-driven pipeline with Apache Kafka ingesting 50M+ events/day, processed through Spark Streaming, and served via real-time Power BI dashboards with geospatial analytics.

Impact

Eliminated all manual data processing. Live dispatch optimization reduced fuel costs by 22% and improved on-time delivery from 78% to 94%.

Industry

Logistics

IndustriesWeServe

Tailored solutions for the unique data and technology needs of each industry.

Manufacturing

Real-time IoT data pipelines connecting MES, ERP, and sensor systems for unified production visibility.

Key Use Cases

01
IoT Pipelines
02
MES Integration
03
Sensor Data

Security&Compliance

Every solution we build meets enterprise security standards from day one — not bolted on after.

Data Encryption at Rest & In Transit

AES-256 encryption at rest and TLS 1.3 in transit across all environments — development, staging, and production.

Role-Based Access Control (RBAC)

Fine-grained access policies with least-privilege defaults ensure teams only access the data they're authorized to see.

Audit Trails & Data Lineage

Complete traceability of every data transformation and access event — who changed what, when, and why.

Regulatory Compliance Built In

Architecture designed for GDPR, HIPAA, SOC 2, and industry-specific frameworks from day one — not bolted on after.

Automated PII Detection & Masking

Sensitive fields are automatically discovered, classified, and masked in non-production environments to prevent data leaks.

Disaster Recovery & Business Continuity

Automated backups with defined RPO/RTO targets and cross-region replication for business-critical data assets.

GDPRHIPAASOC 2ISO 27001

FrequentlyAskedQuestions

Find answers to common questions about our services and approach.

Get a Free Data Engineering Assessment

Our experts will review your current setup and recommend next steps.

Schedule a Consultation