below marketmost similar roles pay hereabove market
This role pays less than
74%
of similar roles. Most pay
$144,375–$214,825
— the blue band above.
At the midpoint, this role pays about
$145k
versus about
$180k
for comparable roles.
Based on 240 similar postings.
Employer
About Ally Financial
Ally Financial is a US-based digital financial services company offering online banking, auto financing, mortgage, and investment products. It is one of the largest all-digital banks in the United States.
Ally Financial currently has
22 open roles
on FindRole.
Listed pay typically runs
$110,000–$180,000
across 22 roles with salary data.
The Manager - Data Engineering will lead a team of developers and analysts within the data technologies development and management space. This role involves managing software development life cycle tasks to design and deliver solutions for system integration, reporting, and support functions. Key responsibilities include performing technical analysis of interfaces and databases, gathering requirements, creating technical specifications, and managing vendor relationships. The position requires expertise in cloud-based data solutions on AWS, specifically using S3, Lambda, and DynamoDB. Candidates must possess skills in dbt, Qlik Replicate, InfoSphere DataStage, and CP4D, alongside proficiency in Python, SQL, and Data Vault modeling. The work focuses on building scalable, auditable data structures and pipelines to support enterprise analytics, reporting, and AI use cases within the insurance business data domain.
Manage a team of data technologies developers to deliver and maintain applications supporting Ally's operations.
Coordinate and oversee SDLC tasks to design and deliver solutions for system integration, reporting, and support.
Perform technical analysis of interfaces, files, databases, and reports to gather requirements and create specifications.
Design high-level and low-level system interfaces and define technology changes for the insurance data ecosystem.
Troubleshoot and support system interfaces while managing vendor relationships for incident resolution and enhancements.
Architect and optimize large-scale data ingestion, transformation, cleansing, and deduplication processes across complex environments.
Lead the design and implementation of enterprise data pipelines using Git, DevOps practices, and modern software engineering.
Embed data governance, metadata, lineage, and security practices into engineering solutions.
What we're looking for
Minimum of 7+ years of relevant experience.
Bachelor's Degree in a relevant field of study or equivalent.
Extensive hands-on experience designing and delivering cloud-based data solutions on AWS, including S3, AWS CLI, Lambda, and DynamoDB.
Strong experience with modern data engineering and integration tools such as dbt, Qlik Replicate, InfoSphere DataStage, and CP4D.
Deep expertise in data modeling, including Data Vault, and designing scalable, auditable, and resilient data structures.
Strong programming and automation skills in Python and other scripting languages.
Proven experience leading the design and implementation of enterprise data pipelines using Git, DevOps practices, and modern software engineering approaches.
8+ years of data management and data analysis experience preferred; Bachelor's degree in Computer Science or Information Systems preferred (preferred); Insurance Business data domain knowledge is preferred (preferred).
Snowflake
AWS
Python
Data Vault
dbt
DataStage
Qlik Replicate
S3
Lambda
Data Modeling
DevOps
Agile
APIs
Data Governance
Data Quality
Metadata
Lineage
Generative AI
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