Data Engineering
Eficens' Data Engineering practice designs and builds the data infrastructure that organisations need to move from raw events to business intelligence. We work across the modern data stack — ingestion, transformation, orchestration, and delivery — implementing pipelines that are observable, testable, and maintainable. Whether you're starting from scratch with a greenfield data platform or untangling an existing spaghetti of scripts and ETLs, our engineers bring structure, documentation, and best practices that make your data a reliable asset rather than a liability.
What we deliver
Data Pipeline Development
Batch and streaming pipelines ingesting data from APIs, databases, event streams, and SaaS platforms into your central data store.
Data Warehouse Design
Dimensional modelling, schema design, and warehouse implementation on Snowflake, BigQuery, or Redshift — optimised for query performance and cost.
ELT / ETL Transformation
dbt-based transformation layers that apply business logic to raw data, with version control, testing, and documentation built in.
Real-Time Streaming
Kafka and Flink-based streaming architectures for use cases requiring sub-second data freshness and high-throughput event processing.
Data Quality & Observability
Automated data quality tests, anomaly detection, and lineage tracking using Great Expectations, Monte Carlo, or custom frameworks.
Analytics Engineering
Semantic layer and metrics store implementation connecting your warehouse to BI tools like Looker, Metabase, and Tableau.
Real outcomes, real clients.
Every engagement is different. Here's how we've delivered for clients across industries with problems like yours.
The challenge
A 3PL provider needed real-time visibility across 14 carrier APIs and 3 warehouse systems — their batch ETL ran nightly, making same-day operational decisions impossible.
What we did
Eficens built a Kafka-based streaming pipeline processing 2.2M events per day with sub-5-second latency. Operations teams can now re-route shipments in real time, reducing late deliveries by 28%.
2.2M
Events processed per day, <5 sec latency
The challenge
A health system had 14 disparate data sources — EHR, billing, lab, pharmacy — with no unified view. BI queries on raw tables took 45+ minutes, making weekly reporting a full-day exercise.
What we did
Eficens built a unified Snowflake warehouse with dbt transformation layers and automated Airflow orchestration. Standard BI queries now return in under 3 seconds and weekly reports run automatically overnight.
900×
Query performance improvement
The challenge
A lending platform had three analysts spending 60% of their time manually pulling data, cleaning spreadsheets, and building the same five reports every week.
What we did
Eficens built a dbt + Airflow pipeline that automates all five reports, applies data quality checks, and delivers validated results to the BI layer by 6am daily. The three analysts now focus entirely on analysis.
3 FTEs
Analyst time freed for high-value work
By the numbers
5×
Faster data pipeline delivery
99.9%
Pipeline uptime SLA
60%
Reduction in data incidents
< 1 hr
Data freshness for critical pipelines
Technology Stack
Further reading
From ETL to ELT: Why the Modern Data Stack Changed the Fundamental Architecture of Data Pipelines
The shift from ETL to ELT wasn't a cosmetic rename. It was a fundamental rethinking of where transformation belongs — and it changed what's possible for data teams of every size.
dbt + Airflow + Snowflake: The Trident of the Modern Data Platform and How to Use It Well
Three tools dominate the modern data stack. Understanding what each one does — and where they overlap and conflict — is the difference between a maintainable platform and an accidental mess.
Pipeline Reliability: The Data Engineering Discipline That Separates Good Platforms from Great Ones
Building a data pipeline is the easy part. Keeping it running reliably at 3am when a source system changes its schema is the hard part. Here's how mature data teams do it.
Ready to get started?
Let's talk about how our Data Engineering practice can help your team move faster.
Talk to our team