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Data Engineering.

Reliable data, ready for analysis and AI.

Our data engineers build pipelines, storage and processing systems that make data from across a business available to its teams and its AI features. Data definitions and quality rules are written as specs first, and pipelines are built and tested against them.

01 · What we deliver

Data foundations for informed decisions and AI.

1Ingest2Transform3Store4AccessAppsEventsFilesTransformClean, join, modelQuality checksCorrect & replayPassTrusted dataAnalyticsProducts
1IngestAppsEventsFiles2TransformTransformClean, join, modelQuality checksCorrect & replayPass3StoreTrusted data4AccessAnalyticsProducts
  1. 01

    Data lakes & warehouses

    Solutions that store structured and unstructured data and optimise retrieval for rapid insight.

  2. 02

    Scalable data pipelines

    Pipelines sized for the data volumes involved, with real-time processing where it is needed.

  3. 03

    Data quality & integrity

    Quality rules written as specs and enforced in the pipeline, with cleansing and validation so data is trustworthy for mission-critical analysis.

  4. 04

    Migration to Snowflake & managed cloud databases

    Move data to Snowflake or managed cloud databases, with validation and plans to maintain access during migration.

  5. 05

    Advanced ETL / ELT

    Transform and organise raw data so it is ready for analysis and for AI features.

  6. 06

    Real-time analytics & streaming

    Streaming solutions that keep the business informed and able to react in the moment.

  7. 07

    Sustainable data practices

    Reduce unnecessary storage and processing when designing data systems.

Trusted data foundations for decisions and AI capabilities.

Define data meaning, quality requirements and the design of reliable pipelines. Draft transformation code from the spec, document source-to-target mappings and generate data validation scenarios.

How we build

02 · Our approach

Engineering in practice.

  1. 01

    Ingest & integrate

    Data from many sources, unified and organised for downstream processing.

  2. 02

    Transform, cleanse & load

    We choose ETL or ELT to suit the platform, then clean and format the data against the quality rules in the spec.

  3. 03

    Store & optimise

    Scalable, fast storage on platforms like Snowflake and managed cloud databases, secured and indexed for retrieval.

  4. 04

    Analyse & insight

    Analyse prepared data to answer business questions and support decisions.