AI Services / Data Engineering

Data engineering services — pipelines you actually trust

We design, build, and operate data pipelines — batch and streaming — with quality gates, observability, and warehouse modeling tuned for cost and speed. Pipelines that hold up under real usage, not just first-pass validation.

50+
Pipelines shipped
10M+
Events processed / day
99.9%
Pipeline uptime
<5min
Pipeline alert response

Why Empiryx

Why teams choose Empiryx for data engineering

Pipeline builders who care about data quality, not just throughput
Airflow, Dagster, Prefect, dbt — picked per your team's maturity
Streaming and batch chosen per workload, not dogma
Warehouse design for cost AND query performance
Data quality checks as part of the pipeline, not after
Observability: pipeline health, SLA breaches, and drift alerts

Expertise

Data engineering skills we specialize in

01

Pipeline engineering

Airflow, Dagster, Prefect — DAGs with retries, observability, and SLAs.

02

Warehouse design

Snowflake, BigQuery, Redshift — modeling for cost and query performance.

03

Streaming

Kafka, Flink, Kinesis — real-time pipelines for dashboards and alerts.

04

Data quality

dbt tests, Great Expectations, and Soda — quality gates as part of the pipeline.

Expertise

Roles & capabilities we specialise in

A deeper look at the specialists we place and the work they ship.

Cloud warehouses

Snowflake, BigQuery, Redshift — modeling for cost and performance.

ETL & ELT

Airflow, dbt, Fivetran, Airbyte — picked per workload.

Streaming

Kafka, Kinesis, Flink — real-time pipelines for dashboards and alerts.

Lakehouses

Iceberg, Delta, Hudi — for teams outgrowing a single warehouse.

Data quality

Great Expectations, Soda, and dbt tests as part of the pipeline.

Cataloging

DataHub, OpenMetadata — discoverability and lineage out of the box.

Industries we serve

Built for high-stakes sectors

Domain-aware engineers who understand your sector's constraints — not just the syntax.

FinTech

Compliance and trade data pipelines

E-commerce

Inventory and customer 360 pipelines

Healthcare

PHI-safe ingestion and warehouse modeling

SaaS

Product analytics and event warehouse builds

FAQ

Answers to common questions

Process

How it works

01

Data audit

We map your sources, the warehouse, and the questions your team needs answered.

02

Pipeline MVP

We ship a working pipeline + first dashboard in 2–4 weeks.

03

Harden

We add data quality checks, observability, and SLA alerts.

04

Operate

We monitor pipeline health, drift, and cost — and iterate against real usage.

Get started

Pipelines that earn the trust of your dashboards

Tell us the sources. We'll bring the orchestrator, the warehouse, and the quality gates.

Let's talk

Tell us what you're building

Share your engineering goals and the Empiryx team will respond within 24 hours with a tailored path forward.