Technology Expertise

Big Data Engineering Services

Build enterprise-grade data infrastructure that scales. Our data engineers design and implement pipelines that process petabytes of data reliably and cost-effectively.

Our Big Data Track Record

45+
Data Projects
50PB+
Data Processed
25+
Data Engineers
99.9%
Pipeline Uptime

What is Big Data Engineering?

Big data engineering involves designing, building, and maintaining the infrastructure needed to collect, store, process, and analyze large volumes of data. We help organizations build modern data platforms that turn raw data into competitive advantage.

  • Data pipeline design and implementation
  • Data lake and data warehouse architecture
  • Real-time and batch data processing
  • Data quality and governance
  • Cloud-native data infrastructure
  • Cost optimization for data workloads

Why Choose Big Data?

Key advantages that make Big Data the right choice for your project.

Scalable Processing

Process petabytes of data with distributed computing frameworks.

Petabyte scale

Real-Time Insights

Stream processing for real-time analytics and decision making.

Sub-second latency

Cost Efficiency

Optimize storage and compute costs with modern architectures.

50%+ cost savings

Data Quality

Ensure data accuracy and consistency across the organization.

99%+ data quality
Use Cases

What We Build with Big Data

Real-world applications and solutions powered by Big Data.

E-commerce

Customer 360 Data Platform

Unify customer data from all touchpoints for personalization and analytics.

  • Unified customer view
  • Real-time personalization
  • Cross-channel analytics
  • Customer segmentation
SparkKafkaSnowflakedbtAirflow
Finance

Risk & Compliance Data Lake

Centralized data platform for risk analytics and regulatory reporting.

  • Regulatory compliance
  • Risk modeling
  • Audit trails
  • Data lineage
DatabricksDelta LakeKafkaGreat ExpectationsAirflow
IoT

IoT Data Processing

Process and analyze high-volume sensor data from connected devices.

  • Real-time monitoring
  • Predictive maintenance
  • Anomaly detection
  • Time-series analytics
KafkaSpark StreamingInfluxDBFlinkTimescaleDB
Media

Content Analytics Platform

Analyze viewing patterns and content performance at scale.

  • Viewership analytics
  • Content recommendations
  • Ad optimization
  • A/B testing
BigQueryDataflowPub/SubVertex AILooker
Our Services

Our Big Data Expertise

Our team of 25+ data engineers has processed over 50 petabytes of data across industries.

Data Pipeline Development

Build reliable, scalable data pipelines for batch and streaming data.

  • ETL/ELT Pipelines
  • Stream Processing
  • Data Orchestration
  • Error Handling

Data Platform Architecture

Design modern data architectures including data lakes and warehouses.

  • Data Lake
  • Data Warehouse
  • Lakehouse
  • Data Mesh

Real-Time Analytics

Enable real-time analytics with stream processing and low-latency queries.

  • Stream Processing
  • Real-time Dashboards
  • Event-Driven
  • CDC

Data Governance

Implement data quality, cataloging, and governance frameworks.

  • Data Quality
  • Data Catalog
  • Lineage
  • Access Control

Technology Stack

Tools, frameworks, and integrations we use with Big Data.

Core Tools

Apache Spark
Unified analytics engine
Apache Kafka
Distributed streaming platform
Apache Airflow
Workflow orchestration
dbt
Data transformation tool
Snowflake
Cloud data warehouse
Databricks
Unified data platform
Delta Lake
Open-source storage layer
Great Expectations
Data quality framework

Integrations

AWS S3Azure Data LakeGoogle Cloud StorageBigQueryRedshiftFivetranAirbyteMonte Carlo

Frameworks

Apache FlinkApache BeamPrefectDagsterApache IcebergApache HudiTrinodbt Core
Success Stories

Big Data Case Studies

Real projects, real results. See what we've achieved with Big Data.

Retail

Enterprise Data Lake

Retail Corporation

Challenge

A major retailer needed to consolidate data from 100+ sources including POS, e-commerce, inventory, and marketing for unified analytics.

Solution

We built a cloud-native data lake on AWS using Spark for processing, Airflow for orchestration, and dbt for transformation. The platform processes 5TB+ daily with full data lineage.

Results

  • 100+ data sources integrated
  • 5TB+ processed daily
  • 80% reduction in time-to-insight
  • $2M annual savings in ETL costs
8 months
$350,000
SparkAirflowdbtSnowflakeAWS S3Great Expectations
Finance

Real-Time Fraud Detection Pipeline

Payment Processor

Challenge

A payment processor needed to detect fraudulent transactions in real-time while processing millions of transactions per hour.

Solution

We implemented a streaming architecture with Kafka and Flink for real-time processing, ML models for fraud scoring, and sub-second response times for transaction decisions.

Results

  • 10M+ transactions/hour processed
  • Sub-100ms fraud scoring
  • 40% improvement in fraud detection
  • $15M annual fraud prevented
6 months
$280,000
KafkaApache FlinkRedisPostgreSQLML ModelsKubernetes
Engagement Models

How We Work Together

Flexible engagement models tailored to your needs.

Data Platform Build

End-to-end data platform design and implementation.

  • Architecture design
  • Pipeline development
  • Data modeling
  • Documentation
Best for:

New data platforms

Data Engineering Team

Dedicated data engineers embedded in your team.

  • Senior engineers
  • Full-time commitment
  • Knowledge transfer
  • Agile delivery
Best for:

Ongoing data initiatives

Data Architecture Consulting

Expert guidance on data strategy and architecture.

  • Assessment
  • Architecture review
  • Technology selection
  • Roadmap
Best for:

Strategic planning

FAQ

Frequently Asked Questions

Ready to Scale Your Data Infrastructure?

Transform your data capabilities with modern big data engineering. Let's discuss your data challenges.