Lead Data Engineer: Remote Azure Lakehouse Migration

Oddball; United States; À distance; USD 110 000 - 145 000; Plein temps

Avantages offerts par ce poste

Fully remote

401(k) plan

Flexible PTO

Paid Holidays

Résumé du poste

Oddball is seeking a Lead Data Engineer to drive the technical approach for migrating legacy data warehouse data and pipelines to an Azure Databricks lakehouse. This role sits on our federal-focused VA team and requires strong leadership in a fully remote environment.

You'll design reusable migration pipelines with Azure Data Factory and Databricks, define reconciliation rules, mentor engineers, and partner with product, QA, and platform teams to ensure data quality and performance.

Qualifications

• Lead data engineering efforts on large migration or modernization programs.
• Deep experience with Databricks or Spark and Azure Data Factory.
• Strong SQL and Python skills.
• Experience moving legacy ETL and data warehouse workloads to the cloud.

Responsabilités

• Set the technical approach for migrating data and pipelines onto the lakehouse.
• Guide migration teams on patterns, reconciliation, and quality gates.
• Design reusable migration pipelines using Azure Data Factory and Azure Databricks.
• Define how source and target data are reconciled to confirm accuracy.
• Resolve the hardest pipeline and performance problems.
• Mentor data engineers and review their work.
• Partner with product, QA, and platform teams.

Connaissances

Leadership

SQL

Python

Remote collaboration

Agile

Formation

Bachelor's Degree

Outils

Azure Data Factory

Azure Databricks

Spark

Delta Lake

Description du poste

Oddball is seeking a Lead Data Engineer to drive the technical approach for migrating legacy data warehouse data and pipelines to an Azure Databricks lakehouse. This role sits on our federal-focused VA team and requires strong leadership in a fully remote environment.

You'll design reusable migration pipelines with Azure Data Factory and Databricks, define reconciliation rules, mentor engineers, and partner with product, QA, and platform teams to ensure data quality and performance.