Data Platform Engineer (102-08SENG-01)
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 55d ago
The date the source published, not the day we noticed it (2026-08-20). Last seen at its source just now.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
Brazil
The description agrees: it names LATAM.
What the ad says
…Open to candidates from all LATAM…
Pay not stated
Similar roles pay $80k–145.5k/yr
Middle 50% of 34 listings that do state pay — Engineering · all levels · Brazil · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Recruitee employer's own board first seen 1h ago · last seen just now
The listing
This role converts a large Azure Data Factory estate into Databricks workflows on AWS. The scope for year one: 2,094 ADF pipelines to migrate — built as reusable templates rather than one-by-one — 9,859 pipeline activities to translate (some map directly, others need rewriting as Lambda or Step Functions), 471 Spark dataflows to move onto Databricks on AWS, and 4 Databricks workspaces (Dev, QA, Pre-prod, Prod) to rehost, including notebook paths and Unity Catalog rewiring. This is a regulated environment, so reconciling migrated data against source systems is part of the definition of done, not an afterthought.
What you will do
Convert Azure Data Factory pipelines into Databricks workflows on AWS, building reusable templates rather than migrating one at a time.
Rehost Databricks workspaces onto AWS and migrate ADLS Gen2 storage to S3.
Rewrite ADF Web Activities as Lambda functions or Step Functions tasks, and replace ADF-specific scaling with native Databricks mechanisms.
Build and tune PySpark transformations for production data volumes.
Replace Azure Synapse Serverless with Databricks SQL Warehouse.
Reconcile migrated data against source systems as part of the definition of done.
Required
Production experience with Databricks: workspaces, jobs and workflows. The central skill for this role.
Strong Spark and PySpark experience for real data volumes, including tuning.
Production-grade Python.
Experience building or migrating Azure Data Factory pipelines, with a solid understanding of the ADF activity model.
AWS data services: S3, Glue, Athena, Lambda and Step Functions.
Advanced SQL, including reading and reasoning about stored procedures.
Professional written and spoken English.
Nice to have
Delta Lake, Unity Catalog, Azure Synapse, Terraform, Airflow/MWAA, dbt, Kafka, Databricks certification, data modeling, Great Expectations, SAS/analytics platform integration, CRM data.
Engagement details
Estimated start date: December 2026
Duration of project: 9 months
EST Time Zone
Open to candidates from all LATAM