Azure Databricks Engineer

Ethereum Technologies LLC; Wilmington (DE); On-site; USD 140,000 - 190,000; Full time

Job summary

Ethereum Technologies is seeking a highly skilled data engineering leader to migrate data pipelines from Informatica to Azure Databricks. You will assess current assets, define the target architecture, and drive a phased migration plan with strong collaboration across business, product, and operations teams.

You will modernize ETL patterns into scalable ELT approaches using PySpark, Python, and Spark SQL, mentoring engineers and ensuring production readiness and data quality throughout the

Qualifications

• Experience leading end-to-end data migration projects.
• Ability to translate source/target mappings into scalable PySpark pipelines.
• Strong collaboration with业务 stakeholders to align migration objectives.

Responsibilities

• Lead the end-to-end migration of data pipelines from Informatica to Azure Databricks.
• Assess current Informatica assets and define target architecture, strategy, and phased plans.
• Drive ELT modernization using Databricks best practices and PySpark-based pipelines.
• Analyze Informatica mappings and convert to PySpark, Python, or Spark SQL equivalents.
• Provide technical leadership across design, standards, testing, and deployment.
• Mentor engineers on Databricks patterns and modern data engineering practices.

Skills

PySpark

Python

SQL

Tools

Informatica PowerCenter

Azure Databricks

Spark SQL

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

• 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.