Hybrid Data Engineer - Azure Pipelines & Data Quality

DLA Piper; Phoenix (AZ); Hybrid; USD 101,000 - 160,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) retirement plan

Hybrid work schedule

Job summary

DLA Piper is seeking a Data Engineer, Solutions & Data to design, build, and operate data pipelines that translate raw data into trusted analytics datasets. The role focuses on governance, data quality, and secure access, consolidating data from multiple sources into a central SQL-based integration point for analytics. The position offers a hybrid schedule in U.S.

offices. Key responsibilities include building ingestion, transformation, and publication pipelines, managing data warehousing with

Qualifications

• Experience designing and operating data pipelines
• Experience with cloud data services and governance
• Strong SQL and Python programming fundamentals
• Ability to work in an Agile Pod Model and collaborate with engineers and analysts
• Familiarity with DataOps concepts and cross-functional teams

Responsibilities

• Build and operationalize data pipelines across heterogeneous environments with SLAs.
• Ingest, transform, and publish data to deliver analytics-ready datasets.
• Consolidate data from multiple sources into a centralized integration point.
• Design and implement data pipelines using Azure data technologies.
• Build and maintain data warehousing with Azure Synapse Analytics.
• Identify, troubleshoot, and resolve data issues to ensure reliability and security.
• Collaborate with engineers, analysts, and stakeholders to deliver data solutions.

Skills

SQL

Python

Data pipelines

Azure Data Factory

Azure Databricks

Azure Event Hubs

SSIS

Azure Synapse Analytics

Data modeling

PowerShell

Java

Scala

Go

DataOps

Cross-functional teams

Education

High School or GED

Bachelor's Degree in Computer Science, Engineering, or related field

Tools

SQL Server

PowerShell

Job description

DLA Piper is seeking a Data Engineer, Solutions & Data to design, build, and operate data pipelines that translate raw data into trusted analytics datasets. The role focuses on governance, data quality, and secure access, consolidating data from multiple sources into a central SQL-based integration point for analytics. The position offers a hybrid schedule in U.S.

offices. Key responsibilities include building ingestion, transformation, and publication pipelines, managing data warehousing with