Azure Databricks Engineer

Machine Learning Technologies, LLC; Wilmington (DE); On-site; USD 120,000 - 180,000; Full time

Job summary

Machine Learning Technologies, LLC is seeking a senior engineer to lead the migration of data pipelines from Informatica to Azure Databricks. The role requires architecting the target state, planning phased execution, and implementing PySpark-based pipelines while modernizing ETL patterns to ELT best practices.

You will provide technical leadership across solution design, code quality, testing strategy, deployment, and production readiness, collaborating with stakeholders to ensure alignment

Qualifications

• Experience migrating data pipelines from Informatica to Databricks.
• Hands-on with PySpark to build scalable pipelines.
• Strong understanding of ELT patterns and modern data engineering.
• Experience with Azure Databricks best practices and Unity Catalog.

Responsibilities

• Lead end-to-end migration of data pipelines, workflows, and integration patterns to Azure Databricks.
• Define migration strategy, target architecture, and phased execution plans.
• Provide technical leadership on design, standards, testing, deployment, and production readiness.
• Mentor engineers on Databricks design patterns and reusable data engineering frameworks.
• Partner with business, architecture, security, and operations to align migration with enterprise priorities.

Skills

Azure Databricks

PySpark

ETL/ELT

Data Pipelines

Cloud Architecture

Tools

Informatica PowerCenter

Oracle

Spark SQL

Job description

• 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.
• E stablish 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

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.