Skip to main content

Data Engineering & Analytics

Unified data platforms, ETL pipelines, and AI-ready architecture.

We build the data infrastructure that powers your business intelligence and AI initiatives. From ETL/ELT pipelines and data lakes to real-time analytics dashboards and AI-ready data architecture — we ensure your data is clean, accessible, and actionable across every platform.

5Capabilities
4Specialized Services
What We Deliver

Our Capabilities

01

Unified Data Platforms

Design and build centralized data platforms that bring together data from Salesforce, AWS, Google Cloud, and third-party systems into a single source of truth. We architect for both analytical and operational workloads.

  • Data lakehouse architecture on AWS (S3 + Athena + Glue) or GCP (BigQuery + GCS)
  • Salesforce Data Cloud for unified customer profiles
  • Master data management and data governance frameworks
  • Data catalog and metadata management
  • Cross-platform data mesh architecture
AWSGoogle CloudSalesforce
Unified Data Platforms
02

ETL/ELT Pipelines

Build reliable, scalable data pipelines that extract, transform, and load data across your systems. Whether batch or real-time, we design pipelines with monitoring, error handling, and data quality checks built in.

  • AWS Glue, Step Functions, and Lambda for ETL
  • Google Dataflow and Cloud Composer for GCP pipelines
  • dbt for SQL-based data transformation
  • Real-time streaming pipelines with Kafka and Kinesis
  • Data quality validation and lineage tracking
AWSGoogle Cloud
ETL/ELT Pipelines
03

Data Lakes & Warehouses

Architect data storage solutions optimized for your workload — from cost-efficient data lakes for raw data to high-performance warehouses for analytics. We design storage layers that balance cost, performance, and accessibility.

  • AWS S3 data lake with Lake Formation governance
  • Google BigQuery serverless data warehouse
  • Amazon Redshift for high-performance analytics
  • Delta Lake and Apache Iceberg for lakehouse patterns
  • Data partitioning, compression, and lifecycle management
AWSGoogle Cloud
Data Lakes & Warehouses
04

Business Intelligence & Visualization

Turn data into decisions with interactive dashboards, automated reports, and embedded analytics. We build BI solutions using Tableau, Looker, CRM Analytics, and custom visualization tools.

  • Tableau dashboards and embedded analytics
  • CRM Analytics (Tableau CRM) for Salesforce insights
  • Looker and Looker Studio for Google Cloud analytics
  • Custom data visualization with D3.js and Recharts
  • Automated report scheduling and distribution
TableauGoogle CloudSalesforce
Business Intelligence & Visualization
05

AI-Ready Data Architecture

Design data architectures specifically optimized for AI and machine learning workloads. We ensure your data is structured, labeled, and accessible for model training, feature engineering, and real-time inference.

  • Feature stores for ML model training and serving
  • Data labeling and annotation pipelines
  • Vector database design for embedding storage and search
  • Data versioning and experiment tracking (MLflow, W&B)
  • Privacy-compliant data pipelines (PII masking, anonymization)
AWSGoogle Cloud
AI-Ready Data Architecture
Case Studies

Data Engineering & Analytics Success Stories

See how we've delivered measurable results with data engineering & analytics.

Legacy Data Warehouse to BigQuery: Real-Time Analytics for 200M+ Records
24 hrs → Real-time
Data Freshness
Logistics & Supply Chain

Legacy Data Warehouse to BigQuery: Real-Time Analytics for 200M+ Records

TransGlobal Logistics

TransGlobal's legacy on-premise data warehouse was hitting capacity limits with 200M+ shipment records, overnight ETL jobs running 14 hours, and analysts waiting until noon for yesterday's data. The BI team maintained 400+ reports in an ageing Cognos installation, with no self-service capability. Real-time visibility into shipment status, fleet utilisation, and supply chain disruptions was impossible, leaving operations teams reactive instead of proactive.

Google BigQueryDataflowLooker StudioVertex AI
Read Case Study
AI-Powered Sales Intelligence with Google Cloud & Salesforce
75% reduction
Meeting Prep Time
Financial Services

AI-Powered Sales Intelligence with Google Cloud & Salesforce

Atlas Capital Group

Atlas, a mid-market investment advisory firm with 300+ relationship managers, had rich but fragmented data across Salesforce, market feeds, custodian platforms, and internal research documents. RMs spent hours manually preparing for client meetings by searching through disconnected systems. The firm had no predictive capabilities for identifying cross-sell opportunities or anticipating client needs, and leadership lacked a unified view of revenue drivers across the business.

Google BigQueryVertex AIGoogle Cloud NLPLooker
Read Case Study
Serverless Data Pipeline & Real-Time Analytics on AWS
8 hours → 30 seconds
Data Latency
Technology

Serverless Data Pipeline & Real-Time Analytics on AWS

Velocity Analytics Inc.

Velocity, a B2B analytics platform processing 500M+ events daily, was running a fragile on-premise ETL pipeline that took 8 hours to produce daily reports. Data latency meant customers were making decisions on stale information. Infrastructure costs were escalating with every new client onboarding, and the engineering team spent 40% of their time on pipeline maintenance rather than product development. The company needed a scalable, real-time data architecture that could grow with their client base while integrating processed insights back into Salesforce for their customer success team.

AWS LambdaAmazon KinesisAmazon RedshiftAmazon S3
Read Case Study