Solutions Engineer, Data - GCS, Data & Analytics

Job Location s US-NH-Portsmouth | US-OH-Columbus | US-MA-Boston | US-IN-Indianapolis | US-TX-Plano

Job :

Position Type:
Full-Time

Job Grade: 19

Department: 083S-13491 GCS - Data & Analytics

Market:
Corporate Center

Referral Bonus Amount: 3500

Minimum Salary: USD $/Yr.

Maximum Salary: USD $/Yr.

Recruiter:
Monica Vesprani

Internal Final date to receive applications: 10/16/26

Referral Bonus Eligible?:
Yes

Responsible for the implementation of technology by engineering clear, comprehensive and integrated data solutions which support business plans and long-term strategies. Consults on the most complex data architecture and data models to improve quality, reliability, and efficiency of data. Provides leadership in reviewing the velocity of the team, presenting continuous improvement opportunities for improved product/team performance.

Responsibilities

Consults on designing and developing programs and tools to support ingestion, curation and provisioning of highly complex enterprise data to achieve analytics, reporting, and data science. Involved in and contributes to development and enhancement of solutions for gaps. Responsible for designing and building highly complex data models and data architecture that improve accessibility, efficiency, governance and data quality that directly impact business results.

Understands and develops business process improvements that address the most complex technology gaps within a single business process. Develops technology enabled recommendations to address gaps within a single business process. Proactively identifies potential impact on business strategy and recommends potential solutions as necessary. Documents existing processes, organizational structures, architectures and external systems. Consults on the appropriate tools to prepare deliverables;

participates in the development of tools and methodologies and adapts them to the organization environment. Manages peer to peer relationships, with colleagues, vendors and external contractors, including offshore functions. Assists with development and execution of cutover plans for simple processes. Assists in post-implementation support, resolving issues and raising defects to appropriate level. Executes transition plan for area of responsibility to the appropriate resource for each phase of the project or initiative.

Transitions the knowledge sharing and transfers ownership to other resources or teams for key deliverables and business processes across a module.

• Bachelor’s or Master’s degree in technical or business discipline or equivalent experience; technical Master`s degree preferred
• Generally, a minimum of 10 years related experience
• Snow Pro Core certification or 3+ year’s experience with Snowflake administration and engineering. Experience with Snowflake Cortex preferred.
• In-depth knowledge of AWS Airflow architectural design and implementation
• Advanced knowledge of Github Copilot and experience leveraging it to build AI assisted workflows
• Advanced knowledge of data architecture patterns, data modeling, normalization and ingest. Experience in working with Cybersecurity domain data sources is preferred.
• Knowledgeable in data engineering languages and tools; proficient in new and emerging technologies. Experience with Python, Lucid Charts, AWS, Coligo, Service Now, Claude Code, PowerBI and SQL are preferred
• Proven ability to design and deliver data products with limited guidance and supervision
• In-depth understanding of layered solutions and designs; in-depth understanding of shared data engineering concepts and product features, as well as security minded
• In-depth knowledge of business operations, objectives and strategies; in-depth understanding of global business and technology trends and the financial services industry
• Highly developed negotiation, consensus building & influencing skills, facilitation and the adaptability to respond to change quickly
• Highly developed oral and written communication skills; strong presentation skills
• Ability to effectively collaborate with all levels of the organization
• AI Engineering:
  Knowledge of AI and agentic frameworks and the related context management patterns, and skilled in implementing solutions with them in a secure, stable, and observable way.