Data Engineering Solutions

We design and build scalable data infrastructure that transforms raw information into business value.

Discuss Your Data Challenges

Our Data Engineering Expertise

Modern Data Stack Implementation

From legacy ETL to modern cloud-native architectures using:

Snowflake Databricks Airflow dbt Fivetran

Streaming Data Solutions

Real-time data processing pipelines with:

Kafka Spark Streaming Flink Kinesis

Data Governance & Quality

Implementing observability and reliability frameworks:

Great Expectations DataHub Collibra Custom Solutions

Data Engineering Case Studies

E-commerce Data Platform Modernization

AWS Snowflake Airflow dbt

Challenge

A fast-growing marketplace was struggling with nightly batch processing windows exceeding 8 hours, preventing timely analytics and business decisions.

Solution

  • Replaced monolithic ETL with modular data pipelines
  • Implemented incremental processing patterns
  • Built real-time clickstream analytics capability
  • Established data quality monitoring framework

Results

  • 70% reduction in processing time (8h → 2.5h)
  • Real-time dashboard capabilities enabled
  • 30% reduction in cloud infrastructure costs

Healthcare Data Interoperability Project

Azure FHIR Server Spark HL7 Transformations

Challenge

A regional hospital network needed to consolidate patient records from 12 legacy systems with incompatible formats, while meeting strict compliance requirements.

Solution

  • Designed FHIR-compliant data model
  • Built transformation pipelines for HL7v2, CCDA, and proprietary formats
  • Implemented de-identification for research datasets
  • Created patient 360° views for care teams

Results

  • Unified records for 500,000+ patients
  • Reduced reporting time from days to hours
  • Enabled cross-facility analytics for the first time

Financial Services Data Lake Implementation

Databricks Delta Lake Kafka Apache Ranger

Challenge

A mid-sized bank needed to consolidate customer data from core banking, loan origination, and mobile apps while maintaining strict audit trails and access controls.

Solution

  • Implemented medallion architecture data lake
  • Designed row-level security framework
  • Built change data capture pipelines from mainframe systems
  • Created self-service analytics environment for business teams

Results

  • 60% faster time-to-insight for business analysts
  • Reduced compliance audit preparation from weeks to days
  • Enabled new customer segmentation models

Ready to Transform Your Data Infrastructure?

Our data engineering team can help you build pipelines that scale with your business.

Email Our Data Team