Ortem Technologies
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    Data Engineering

    Data Engineering Services

    Pipelines, Warehouses & Real-Time Streaming — Built to Be Trusted

    We build the data infrastructure your analytics and AI initiatives depend on. Reliable pipelines, well-modelled warehouses, real-time streaming, and the DataOps practices that keep it all trusted and maintained.

    AI & ML Solutions

    What We Build

    Data Warehouse Design & Build

    Architect and implement cloud data warehouses on Snowflake, BigQuery, or Redshift. Dimensional modelling, slowly changing dimensions, and star-schema design built for analytics performance.

    ETL/ELT Pipeline Development

    Build reliable data pipelines that ingest from SaaS tools, databases, APIs, and event streams. dbt transformations, incremental loads, and automated data quality checks built in.

    Real-Time Streaming

    Design event-driven data architectures using Apache Kafka, AWS Kinesis, or Pub/Sub. Sub-second latency for operational analytics, fraud detection, and real-time dashboards.

    Data Platform Modernization

    Migrate from legacy warehouses and brittle ETL scripts to a modern lakehouse or cloud-native data platform. Maintain business continuity throughout the migration.

    Analytics Engineering

    Build a semantic layer your analysts can trust: dbt models, metric definitions, and documentation that turns raw warehouse tables into business-ready data products.

    DataOps & Data Quality

    Automated data quality checks (Great Expectations, dbt tests), pipeline monitoring, alerting on data freshness and schema changes, and full data lineage visibility.

    Common Engagements

    Consolidate data from 10+ SaaS tools into one warehouse
    Replace overnight batch jobs with near-real-time pipelines
    Build the data foundation for an ML model
    Migrate from on-premise Oracle/Teradata to Snowflake
    Create a single customer view across CRM, product, and billing
    Enable self-serve analytics for non-technical teams
    Build a product analytics pipeline from event streams
    Automate reporting that currently requires manual SQL

    Our Data Engineering Stack

    Warehouses

    Snowflake, BigQuery, Redshift

    Transformation

    dbt, Spark, pandas

    Orchestration

    Apache Airflow, Prefect, Dagster

    Streaming

    Kafka, Kinesis, Pub/Sub

    Ingestion

    Fivetran, Airbyte, custom connectors

    Data Quality

    Great Expectations, dbt tests, Monte Carlo

    Frequently Asked Questions

    Related Services

    AI & ML SolutionsApp ModernizationCloud & DevOpsCloud Cost Optimisation

    Further Reading

    ETL vs ELT PipelinesData Warehouse vs Data LakeCase StudiesOur PortfolioFAQs

    Ready to Build a Reliable Data Foundation?

    Tell us your current data stack and what's breaking down. We'll review it and propose a target architecture — in a free 45-minute discovery call.

    Also see: AI & ML Solutions · Cloud & DevOps · Application Modernization