Azure Databricks Engineer

MACHINE LEARNING TECHNOLOGIES LLC; Wilmington (DE); Presencial; USD 140.000 - 170.000; Jornada completa

Descripción de la vacante

MACHINE LEARNING TECHNOLOGIES LLC is seeking an Azure Databricks Engineer in Wilmington, DE. The role focuses on migrating from Informatica to Azure Databricks, designing the target state, and delivering scalable ELT data pipelines using PySpark and Spark SQL in a Databricks environment.

The position requires technical leadership, collaboration with enterprise stakeholders, and ensuring data quality, performance, and observability through the migration lifecycle.

Responsabilidades

• Lead the end to end migration of data pipelines, workflows, and integration patterns from Informatica to Azure Databricks.
• Assess current state Informatica assets and define target state architecture, migration strategy, and phased execution plans.
• Drive modernization of ETL patterns into scalable ELT and data engineering approaches aligned with Azure Databricks best practices.
• Analyze and interpret complex Informatica PowerCenter mappings and build equivalent PySpark based pipelines in Azure Databricks.
• Assess Oracle database level stored procedures and determine migration/refactor/recreation in Databricks using PySpark/Spark SQL.
• Provide technical leadership across solution design, engineering standards, testing strategy, deployment, and production readiness.
• Partner with stakeholders to align migration outcomes with enterprise priorities.
• Establish migration success criteria covering data quality, reconciliation, performance, resilience, observability, and business continuity.
• Identify delivery risks and drive mitigations; guide cutover, stabilization, and post-migration optimization.
• Mentor engineers on Databricks design patterns and modern data engineering practices

Descripción del empleo

Job Overview

• Job ID: J53392
• Job Title: Azure Databricks Engineer
• Location: Wilmington, DE
• Duration: 22 Months + Extension
• Domain Exposure: Pharmaceuticals
• Work Authorization: US Citizen,Green Card,OPT-EAD,CPT,H-1B,H4-EAD,L2-EAD,GC-EAD
• Client: To Be Discussed Later
• Employment Type: W-2, 1099, C2C

Key Responsibilities

• Lead the end to end migration of data pipelines, workflows, and integration patterns from Informatica to Azure Databricks.
• Assess current state Informatica assets and define target state architecture, migration strategy, and phased execution plans. The current environment is based on Informatica PowerCenter 10.4.1 running batch ETL workloads, with Oracle as both the source and target database. The target state platform is Azure Databricks (Runtime 14.4 LTS) with Unity Catalog, Delta Live Tables (DLT), and ADLS Gen2.
• Drive modernization of ETL patterns into scalable ELT and data engineering approaches aligned with Azure Databricks best practices.
• Analyze and interpret complex Informatica PowerCenter mappings, including transformations, lookups, joins, filters, routers, and expression logic, and build equivalent PySpark based pipelines in Azure Databricks.
• Assess Oracle database level stored procedures, functions, and packages that are invoked by or tightly coupled with Informatica workflows, and determine whether to migrate, refactor, or recreate that logic within Databricks using PySpark, Python, or Spark SQL.
• Provide technical leadership across solution design, engineering standards, code quality, testing strategy, deployment, and production readiness.
• Partner with business, product, architecture, infrastructure, security, and operations stakeholders to align migration outcomes with enterprise priorities.
• Establish migration success criteria covering data quality, reconciliation, performance, resilience, observability, and business continuity.
• Identify delivery risks, dependencies, and technical constraints early, and drive mitigation plans through execution.
• Guide cutover, stabilization, and post migration optimization to ensure sustainable platform adoption and operational excellence.
• Mentor engineers and technical teams on Databricks design patterns, reusable frameworks, and modern data engineering practices

Equal Opportunity Employer

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.