Data Engineering & Big Data

What We Build

End-to-End Data Platforms

ETL / ELT Pipelines

Robust data transformation workflows that extract from any source, transform at scale, and load into your destination of choice with full observability.

Batch & micro-batch processing
Schema evolution & data validation
Incremental & full-load strategies
Data quality checks at every stage
Lineage tracking & audit trails

Data Lakes & Lakehouses

Centralized repositories that store structured and unstructured data at any scale, enabling analytics, ML, and real-time queries on a unified platform.

Delta Lake / Apache Iceberg
S3, ADLS, GCS storage layers
Schema-on-read flexibility
ACID transactions on data lakes
Unified batch & streaming queries

Real-Time Streaming

Process millions of events per second with sub-second latency. From IoT telemetry to financial transactions, we build streaming platforms that never miss a beat.

Apache Kafka event streaming
Spark Structured Streaming
Flink for complex event processing
Real-time dashboards & alerts
Exactly-once processing guarantees

Data Warehousing & Analytics

Modern cloud data warehouses optimized for fast analytical queries across terabytes of data, powering BI dashboards and decision-making tools.

Snowflake / BigQuery / Redshift
Star & snowflake schema modeling
Materialized views & query optimization
BI tool integration (Tableau, Looker, Power BI)
Cost optimization & auto-scaling

Technology

Our Data Stack

Battle-tested technologies chosen for reliability, performance, and community strength.

Processing Engines

Apache Spark Distributed batch & stream processing at petabyte scale. PySpark, Spark SQL, MLlib.

Apache Hadoop HDFS, MapReduce, and YARN for massive distributed storage and computation.

Apache Flink Stateful stream processing with exactly-once semantics and low-latency.

Orchestration & Workflow

Apache Airflow DAG-based workflow orchestration for complex ETL scheduling and monitoring.

dbt (Data Build Tool) SQL-first transformations with testing, documentation, and lineage built in.

Prefect / Dagster Next-generation orchestrators with native Python, observability, and asset-based pipelines.

Messaging & Streaming

Apache Kafka Distributed event streaming for high-throughput, real-time data pipelines and integration.

RabbitMQ Message broker for reliable asynchronous communication between services.

Redis Streams In-memory data structure store for caching, sessions, and lightweight streaming.

Storage & Warehousing

Snowflake / BigQuery / Redshift Cloud-native analytical data warehouses for OLAP workloads at any scale.

S3 / ADLS / GCS Object storage as the foundation for data lakes with cost-effective tiered storage.

Delta Lake / Apache Iceberg Open table formats bringing ACID transactions, time-travel, and schema evolution to data lakes.

Architecture

Data Pipeline Patterns

We implement proven architectural patterns tailored to your data volume, velocity, and variety.

01

Batch Processing

High-volume nightly or hourly jobs that process terabytes of historical data for warehousing, reporting, and model training.

Sources → Spark / Hadoop → Transform → Data Warehouse

SparkHadoopAirflowdbtSnowflake

02

Stream Processing

Real-time event processing for use cases where milliseconds matter — fraud detection, IoT, live analytics, and instant personalization.

Events → Kafka → Flink / Spark → Real-Time Store

KafkaFlinkSpark StreamingRedisElasticsearch

03

Lambda Architecture

The best of both worlds — combine batch accuracy with streaming speed. A serving layer merges results for complete, up-to-date views.

Ingestion → Batch + Speed → Serving Layer → Query

SparkKafkaDelta LakePrestoDruid

04

Modern Data Mesh

Domain-oriented, decentralized data ownership with federated governance. Each team owns and publishes their data as a product.

Domain Teams → Data Products → Self-Serve Platform → Consumers

Data CatalogAPIsdbtGovernanceSelf-Service

At Scale

Numbers That Matter

PB+

Data Processed

Petabyte-scale data lakes and warehouses with optimized storage tiers and compression.

1M+

Events / Second

Real-time streaming pipelines ingesting millions of events with sub-second processing latency.

500+

Data Sources Integrated

APIs, databases, files, streaming sources — we connect to virtually any data source.

60%

Cost Reduction

Query optimization, partitioning strategies, and storage tiering that cut cloud costs dramatically.

Governance

Data Quality & Compliance

Enterprise data demands enterprise governance. We build quality, security, and compliance into every layer.

Data Security

Encryption at rest & in transit, column-level masking, and role-based access control.

Data Quality

Automated tests, anomaly detection, freshness monitoring, and data contracts between teams.

GDPR / CCPA Ready

Privacy-by-design architectures with data anonymization, consent management, and right-to-delete.

Data Catalog

Searchable metadata, business glossaries, and automated documentation for every dataset.

Lineage Tracking

End-to-end visibility of how data flows, transforms, and arrives at every destination.

Observability

Pipeline health dashboards, SLA monitoring, alerting, and automated incident response.