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Practice 04

ETL & Data Integration

Modern ELT, CDC and streaming pipelines landing data into Snowflake, Databricks, BigQuery and Redshift — with dbt, lineage, observability and FinOps baked in from day one.

Data pipelines, treated as production software — not weekend scripts.

ByteWave engineers ETL/ELT as a production discipline: versioned, tested, monitored, observable and cost-aware. We replace hand-rolled cron jobs and fragile Informatica workflows with reproducible, lineage-tracked pipelines that the data team — and the auditor — can actually trust.

What we deliver

  • 01
    Modern ELT with Fivetran / Airbyte 300+ connectors into Snowflake / Databricks / BigQuery / Redshift, with schema drift, incremental loads and zero infrastructure to manage.
  • 02
    dbt transformations at scale Project structure, sources, exposures, tests, snapshots, tags, CI/CD, dbt Cloud / dbt-core, multi-project orchestrations.
  • 03
    CDC streaming with Kafka / Kinesis / Pub-Sub Debezium, Oracle GoldenGate, HVR, AWS DMS, Azure Data Factory — landing change events into Delta Lake / Snowflake in seconds.
  • 04
    Orchestration with Airflow / Prefect / Dagster Kubernetes-native Airflow, Prefect Cloud, Dagster assets. Event-driven, idempotent, observable, with PagerDuty integration.
  • 05
    Legacy ETL modernization Informatica PowerCenter, Talend, DataStage, SSIS → modern ELT. We rewrite jobs, not just deploy them to new servers.
  • 06
    Data observability & lineage Monte Carlo, Soda, Great Expectations, Datafold, OpenLineage + Marquez, Unity Catalog, Snowflake Horizon Catalog.
  • 07
    DataOps & FinOps CI/CD for data, test coverage SLAs, warehouse cost monitoring, query optimization, dynamic tables / materialized views.
  • 08
    Reverse ETL Hightouch / Census / Polytomic pushing Snowflake / Databricks models back into Salesforce, HubSpot, ServiceNow, Marketo.

Patterns we ship

Medallion architecture (Bronze / Silver / Gold), Data Vault 2.0, Kimball dimensional, One Big Table, streaming-first, lakehouse (Delta / Iceberg / Hudi), semantic layer (Cube / dbt Semantic / LookML). We choose the pattern that fits the business problem — not the one that’s trending on LinkedIn.

Outcomes you can measure

  • Data freshness from 24 hours → 5 minutes.
  • Pipeline failure rate <0.5%, MTTR <30 min.
  • Warehouse cost per query cut 38% with query tuning + dynamic tables.
  • Analyst time-to-insight reduced 4×.
  • SOC 2 / ISO evidence collection automated end-to-end.

ETL & Data Integration

Bring the brief.

ByteWave will scope the program and put a solution architect on it within the week.

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