Data Engineering Consulting & Implementation Services
Expert data engineering consulting from a team that builds and scales production data platforms. BigData Boutique helps engineering teams design, implement, and optimize data pipelines, streaming architectures, and analytics infrastructure — from Kafka and Flink to Iceberg and ClickHouse.
Our Data Engineering Services
We bring deep, hands-on experience across the modern data stack — from ingestion and transformation to storage, processing, and analytics — so your team can focus on delivering value instead of fighting infrastructure.
Data Pipeline Architecture
Design and implementation of robust data pipelines — batch ETL, real-time streaming, or hybrid ELT patterns processing billions of events per day
Real-Time Streaming
Streaming architectures with Apache Kafka and Apache Flink — event-driven microservices, real-time analytics, and sub-second data processing
Data Lakehouse & Storage
Modern lakehouse architectures with Apache Iceberg, Delta Lake, and open table formats — consolidating warehouses, reducing costs, and enabling cross-engine interoperability
Analytics Infrastructure
Purpose-built analytics platforms with ClickHouse, Elasticsearch, and OpenSearch — powering dashboards, reporting, observability, and product-facing analytics at scale
Migration & Modernization
Migrate from fragile cron-based scripts and monolithic ETL jobs to modern, observable, and scalable pipeline architectures — without disrupting existing workloads
Cost & Performance Optimization
Audit existing pipelines and storage layers, identify inefficiencies, and implement changes that reduce cloud infrastructure costs and improve throughput
Technologies We Work With
| Category | Technologies |
|---|---|
| Stream Processing | Apache Kafka, Apache Flink, Kafka Connect, Kafka Streams |
| Batch & ETL | Apache Spark, dbt, Apache Airflow |
| Lakehouse & Storage | Apache Iceberg, Delta Lake, Databricks, Apache Hudi |
| Analytics Engines | ClickHouse, Elasticsearch, OpenSearch |
| Cloud Platforms | AWS (Glue, EMR, Kinesis, Redshift), GCP (BigQuery, Dataflow), Azure (Synapse, Data Factory) |
| Data Integration | Airbyte, Fivetran, custom connectors |
We are technology-agnostic. We recommend and implement the tools that fit your requirements — not the ones that generate the most vendor revenue.
Why Choose BigData Boutique for Data Engineering?
Deep Specialization
Our team includes recognized experts in search, streaming, analytics, and distributed systems. We contribute to open-source projects and speak at industry conferences.
Production Mindset
We design for reliability, observability, and operational simplicity. Every architecture decision accounts for what happens at 3 AM when something breaks.
End-to-End Delivery
From initial architecture review through implementation and handoff, we stay involved until the system is running well and your team is confident maintaining it.
Proven Track Record
Our clients include Fortune 100 companies and fast-growing startups. We have delivered data engineering solutions across financial services, e-commerce, cybersecurity, and healthcare.
How We Work
1
Discovery & Assessment
We audit your current data infrastructure — pipelines, storage, processing patterns, and pain points — to identify opportunities and risks.
2
Architecture Design
We design an optimized data architecture tailored to your workloads — technology selection, pipeline topology, storage strategy, and cost modeling.
3
Implementation
Our engineers build hands-on alongside your team — pipelines, integrations, migrations, and infrastructure-as-code — with production-grade quality from day one.
4
Handoff & Support
Documentation, knowledge transfer, and optional ongoing support to keep your data platform healthy, performant, and cost-efficient.
Frequently Asked Questions
We provide end-to-end data engineering consulting including pipeline architecture, real-time streaming with Kafka and Flink, data lakehouse design with Apache Iceberg, analytics infrastructure with ClickHouse and OpenSearch, cloud platform optimization, and legacy pipeline modernization.
We work across the modern data stack: Apache Kafka, Apache Flink, Apache Spark, Apache Iceberg, Delta Lake, ClickHouse, Elasticsearch, OpenSearch, dbt, Airflow, Databricks, and all major cloud platforms (AWS, GCP, Azure). We are technology-agnostic and recommend the best fit for your requirements.
Yes — this is one of our most common engagements. We help teams migrate from fragile cron-based scripts, monolithic ETL jobs, and legacy Hadoop workloads to modern, observable, and scalable pipeline architectures without disrupting existing workloads.
We audit your pipeline architecture, storage layers, compute usage, and cloud configuration. By right-sizing resources, implementing efficient data tiering, optimizing query patterns, and eliminating redundant processing, we consistently deliver significant cost reductions.
Absolutely. For startups and growth-stage companies building their first data platform, we provide architecture guidance and hands-on implementation. We help you avoid the common pitfalls that lead to costly rework down the line.
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