Sr. Analyst - Data Management

General information Career area Technology Work Location(s) 2911 Lake Vista Drive, TX Remote? No  # 21657 Posted Date 02-05-26 Working time Full time Ally and Your Career Ally Financial only succeeds when its people do - and that’s more than some cliché people put on job postings. We live this stuff! We see our people as, well, people - with interests, families, friends, dreams, and causes that are all important to them.

Our focus is on the health and safety of our teammates as well as work-life balance and diversity and inclusion. From generous benefits to a variety of employee resource groups, we strive to build paths that encourage employees to stretch themselves professionally. We want to help you grow, develop, and learn new things. You’re constantly evolving, so shouldn’t your opportunities be, too?

Ally designates roles as (1) fully on-site, (2) hybrid, or (3) fully remote. Hybrid roles are generally expected to be in the office a certain number of days per week as indicated by your manager. Your hiring manager will discuss this role's specific work requirements with you during the hiring process. All work requirements are subject to change at any time based on leader discretion and/or business need.

Opportunity

At this time, Ally will not sponsor a new applicant for employment authorization for this position.

Are you passionate about data management and data analytics? Do you possess first‑hand experience in cloud technologies, data warehousing, data integration? Do you believe in modern software development methods, teamwork, creativity, and collaboration within a diverse development environment to produce the next generation of data - analytics platforms and services?

If so, then we are interested in talking to you! Ally is seeking a Sr. Analyst - Data Management within Ally's Data Solutions Support team. The ideal candidate will have personal experience implementing data lakes, data analytics, and master data management solutions, including data ingestion, data homogenization - data preparation, data quality checking and management, structured and unstructured data processing, and analytics engineering.

Experience with modern self‑service data capabilities, data management and governance, data modeling architecture is also a plus. Candidates having strong analytical skills, hands on development experience, strong SQL skills, ability to multi‑task, and strong verbal and written communication skills will be best suited for the team.

• Responsible for developing curated semantic layers for the auto business to support analytics engineering and AI product enablement
• Develop and maintain pipelines; partner with data engineering to deploy to Oracle and Snowflake.
• Apply data warehousing principles to design reliable, performant models.
• Extract and reconcile data from traditional and cloud warehouses for executive and operational insights.
• Create clean, tested, well‑documented data layers to power AI use cases (Cortex search, agentic models).
• Validate AI outputs; curate a library of “Verified Queries” and enable fuzzy search via Cortex.
• Write and troubleshoot complex SQL; working knowledge of Python and dbt.
• Stay current on industry trends and lead data/analytics platform innovation.
• Collaborate cross‑functionally to translate needs into tools, metrics, and visualizations.
• Operate within Agile; define/prioritize technical stories and manage multiple projects with clear status and risk communication.
• Metadata integration, quality checks, tags and other steps required to stand up a complete semantic layer that can be used as input for BI or AI products
• Able to do requirement gathering, documenting business metrics, lineage etc.,

• 3 years of relevant experience required, 5 years of relevant experience preferred.
• High school diploma required, Bachelor's degree preferred. With a preferred field of study in Computer Science, Data Management, Data Science, Management Information System, Business Analytics
• Strong organizational, analytical, and interpersonal skills
• RDBMS – Snowflake, Oracle, SQL Server
• Programming Languages/Tools - SQL, Python, DBT
• Data platforms - AWS,…