Data Engineer - Reinvention Centers

Accenture

Hybrid

Quick summary

Work type: Hybrid
Location: Dallas, TXColumbus, OH
Salary: $70,350–$205,800 / yr
Posted: 5 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $173k

This role $138k

$53k most similar roles pay here $228k

This role pays less than 74% of similar roles. Most pay $135,000–$211,200 — the shaded band above. At the midpoint, this role pays about $138k versus about $173k for comparable roles.

Based on 240 similar postings.

Employer

About Accenture

Accenture is a leading global professional services company specializing in IT, strategy, consulting, and operations, with a strong focus on digital transformation, cloud computing, and artificial intelligence.

Accenture currently has 126 open roles on FindRole.

Listed pay typically runs $94,400–$220,400 across 85 roles with salary data.

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View all roles at Accenture

At a glance

TL;DR · Data Engineer - Reinvention Centers

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As a senior data engineer on the Azure team at Accenture, you will lead the design and optimization of scalable data pipelines using tools like Azure Data Factory, Databricks, and Synapse Analytics. Your daily tasks include monitoring pipeline performance, troubleshooting issues, and ensuring high-quality data delivery in hybrid cloud environments. You will collaborate with cross-functional teams to align data engineering solutions with business objectives, provide mentorship on best practices, and contribute to the continuous improvement of Azure platform governance. The role requires expertise in Python or PySpark for distributed data processing, experience with CI/CD pipelines like Azure DevOps, and a strong understanding of data modeling and warehousing. This position offers opportunities to work on complex enterprise projects, enhancing your skills while supporting Accenture’s clients across various industries.

Skills

Azure Azure Data Factory Azure Databricks Azure Synapse Analytics Python PySpark Azure DevOps CI/CD SQL ETL Data Modelling Kafka API Integration Microservices Cloud Database Services Data Quality Data Governance Monitoring Terraform PostgreSQL

What you'll do

Lead the design and optimization of scalable data pipelines on Azure using Azure Data Factory and Databricks.
Monitor pipeline performance and manage incidents to maintain SLAs in production environments.
Provide technical guidance on Azure data engineering best practices to team members.
Collaborate with stakeholders to define data engineering use cases and prototype architectures.
Analyze and troubleshoot data processing issues to ensure high-quality, reliable systems.
Integrate AI agents using Azure AI Foundry into enterprise data workflows for enhanced capabilities.

What we're looking for

Minimum 2 years of experience designing and optimizing scalable data pipelines on Azure.
Strong expertise in Azure Data Factory, Azure Databricks, and Azure Synapse Analytics for complex workflows.
At least 1 year of hands-on experience with data pipeline operations and maintenance.
Proficiency in integrating data pipelines with enterprise APIs and deploying via CI/CD tools.
Experience programming in Python or PySpark for cloud-based distributed data processing.
Demonstrated ability to ensure high data quality, lineage, and governance across platforms.

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