Freelance › Freelancers services › Software development › ELT pipelines with Fivetran and Airbyte: managed connectors into your warehouse
ELT pipelines with Fivetran and Airbyte: managed connectors into your warehouse
Service description
I build automated ELT pipelines that pull data out of your apps and databases and land it in your warehouse without you ever touching a cron job again. Working mostly with Fivetran and Airbyte, I connect the sources your business actually runs on: payment systems, CRMs, ad platforms, product analytics, support desks, and production Postgres or MySQL replicas. The goal is simple and boring in the best way: fresh, trustworthy tables that appear on schedule, so your analysts and dashboards stop waiting on manual exports and stale spreadsheets.
My approach starts with the sync mechanics that make or break a pipeline. I set up incremental replication with proper primary keys and cursors so you move only changed rows instead of re-scanning huge tables every hour. I handle schema drift up front, deciding how new columns, renamed fields, and type changes propagate downstream without breaking the models built on top. I add deduplication, history modes where you need slowly changing dimensions, and sensible sync frequencies tuned to how often each source really changes, which keeps both latency and connector costs under control.
Once data is landing reliably, I make the whole thing observable and maintainable. That means alerting on failed or delayed syncs, row-count and freshness checks, and clear runbooks so a broken connector is a five-minute fix rather than a fire drill. I also wire in the downstream transformations, staging and mart layers, so the raw synced schemas become clean, documented tables ready for BI. You get pipelines that quietly do their job, plus documentation and monitoring that let your team trust the numbers.
— Fivetran and Airbyte connector setup, tuning, and cost optimization
— Incremental syncs, schema-change handling, and deduplication
— Monitoring, freshness and row-count checks, failure alerting
— Downstream staging and mart transformations for BI-ready tables
My approach starts with the sync mechanics that make or break a pipeline. I set up incremental replication with proper primary keys and cursors so you move only changed rows instead of re-scanning huge tables every hour. I handle schema drift up front, deciding how new columns, renamed fields, and type changes propagate downstream without breaking the models built on top. I add deduplication, history modes where you need slowly changing dimensions, and sensible sync frequencies tuned to how often each source really changes, which keeps both latency and connector costs under control.
Once data is landing reliably, I make the whole thing observable and maintainable. That means alerting on failed or delayed syncs, row-count and freshness checks, and clear runbooks so a broken connector is a five-minute fix rather than a fire drill. I also wire in the downstream transformations, staging and mart layers, so the raw synced schemas become clean, documented tables ready for BI. You get pipelines that quietly do their job, plus documentation and monitoring that let your team trust the numbers.
— Fivetran and Airbyte connector setup, tuning, and cost optimization
— Incremental syncs, schema-change handling, and deduplication
— Monitoring, freshness and row-count checks, failure alerting
— Downstream staging and mart transformations for BI-ready tables
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