below marketmost similar roles pay hereabove market
This role pays more than
59%
of similar roles. Most pay
$137,450–$214,000
— the blue band above.
At the midpoint, this role pays about
$194k
versus about
$176k
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
245 open roles
on FindRole.
Listed pay typically runs
$94,400–$266,300
across 187 roles with salary data.
The Data Engineering, Management & Governance Manager joins the Data & AI organization to own the technical integrity and delivery of strategic AI insights platforms. You will design and maintain intelligent data platforms that ingest, model, and govern enterprise data across distributed environments, translating complex data into measurable business value. Key responsibilities include architecting data fabric solutions, building ETL/ELT pipelines, and managing platform versioning and ontology design. You will utilize technologies such as Snowflake, Databricks, Azure Synapse, BigQuery, and Palantir Foundry, while integrating with Salesforce CRM. The role requires proficiency in Python, SQL, and streaming architectures like Apache Kafka. You will solve technical problems related to data quality, metadata lineage, and automated KPI extraction to support whitespace identification and revenue growth insights within complex enterprise environments.
Design and implement enterprise data fabric solutions to provide unified access to distributed data across multi-cloud environments.
Build and maintain strategic AI insights platforms, managing technical builds, versioning, schema evolution, and platform integrity.
Integrate AI platforms with enterprise systems like Salesforce and Palantir Foundry to enable automated KPI measurement and tracking.
Develop data models and ontologies that structure pipeline data for downstream AI and analytics workflows.
Establish data quality governance, security protocols, and metadata lineage to ensure platform outputs are trustworthy and auditable.
Translate business requirements into technical platform data models and AI-powered workflows for clients.
Create reusable data assets, pipeline templates, and reference architectures to accelerate delivery for future client engagements.
Research and evaluate emerging cloud data platforms and AI integration patterns to advance technical solution quality.
What we're looking for
Must have a minimum of 5 years of experience in data architecture, enterprise data engineering, or AI platform delivery.
Must have experience architecting data fabric solutions including data virtualization, active metadata management, knowledge graphs, and automated data integration.
Must have experience with cloud data platforms such as Snowflake, Databricks, Azure Synapse, or BigQuery.
Must have experience with data integration, ETL/ELT pipelines, and metadata and lineage tooling.
Must have experience designing API and streaming architectures for real-time data delivery.
Must have experience with enterprise CRM or operational platform integration, such as Salesforce, in a data engineering or AI context.
Must be proficient in Python and/or SQL for pipeline development, data transformation, and platform automation.
Snowflake
BigQuery
dbt
Airflow
Data Architecture
Data Warehousing
ETL
ELT
Data Lakehouse
Parquet
Iceberg
Data Dog
Anomalo
Data Science
Advanced Analytics
Data Quality
Data Privacy
AWS
S3
Lambda
DynamoDB
Python
SQL
dbt
Qlik Replicate
InfoSphere DataStage
CP4D
Data Vault
Git
DevOps
Agile
SCRUM
Kanban
API Development
Data Warehousing
Data Modeling