Job Description Job Description
Client: M&T Bank Job #: 2881 Job Title: Data Solution Architect Location: Remote w/ travel to Buffalo, NY required every 4 to 6 weeks' (mandatory no exceptions); Travel & lodging expenses will be reimbursed Duration: 6 -month contract W2 Pay Rate: Up to $80.00/hr. target on W2 ONLY (there is some wiggle room w/ the rate BOE / $4.50 to $5.00/hr. W2 referral fee / these roles are not C2C or 1099 eligible) Note: No visa sponsorship/transfer legally authorized to work in the US without visa sponsorship/transfer now or in the future (actual visa card must be valid for the next 24 -months / No H1B or OPT) NOTES FROM MANAGER/REQUIRED SKILLS & EXP.: This posting is for a Data Solution Architect. Eastern/Central time zones required. Travel to Buffalo, NY or Wilmington, DE required once every 4-6 weeks on average. Candidate should have exceptional communication skills and hand on experience in designing, building, and solutioning data related solutions. Candidate should have previous experience as a solution architect and should be able to articulate tangible architecture artifacts that they have personally produced. Solution Architect for Data (someone who can get into the full details of data systems/design). Skill Set 1: Design scalable, secure, and governed data solutions across platforms Skill Set 2: Hands-on experience with modern data ecosystems, integration patterns, and analytics platforms Skill Set 3: Exceptional ability to translate complex technical concepts into clear business outcomes Can this role be fulfilled remotely? Yes Job Title: Data Solution Architect Location: Buffalo, New York (Preferred) / Remote (Will be expected to travel to Buffalo, NY every 4-6 weeks with Monday through Thursday in office; travel expense reimbursed by M&T) Department: Enterprise Architecture Reports To: Enterprise Architect for Data, Analytics & AI Job Summary The Data Solution Architect is responsible for designing and delivering enterprise-grade data platforms and solutions that enable advanced analytics and business intelligence. This role requires deep expertise in data engineering, cloud-native architecture, and modern data technologies. The architect will work closely with engineering, product, and compliance teams to build secure, scalable, and regulatory-compliant data solutions. All solutions must align with the principles, standards, and reference architectures established by the Enterprise Architecture function, ensuring consistency, interoperability, and strategic fit across the organization.
Key Responsibilities - Solution Architecture: Architect and deliver cloud-based data platforms (e.g., Azure Data Lake) and scalable data pipelines using technologies such as Databricks, Kafka, etc.
- ETL/ELT Frameworks: Develop and implement ETL/ELT frameworks for ingesting, transforming, and integrating data from diverse sources, including legacy financial systems, SaaS platforms, and real-time data streams.
- Data Platform Deployment: Design and oversee deployment of data warehouses, lakehouses, and analytics sandboxes to support business intelligence, machine learning, and reporting needs inclusive of Power BI and Snowflake.
- Data Governance: Define and enforce data governance, metadata management, and data quality standards in accordance with Enterprise Architecture guidance and regulatory requirements.
- Enterprise Architecture Collaboration: Collaborate with Enterprise Architecture to ensure all solutions adhere to architectural standards, reference models, and technology roadmaps.
- Technology Evaluation: Lead technical evaluations and proof-of-concept projects for emerging data technologies (e.g., real-time analytics, data mesh, AI/ML platforms).
- Technical Documentation: Produce deliverables such as architecture diagrams, data flow maps, security models, and technical documentation for solution handoff and operational support.
- Agile/DevOps Leadership: Guide Agile/DevOps teams in implementing CI/CD pipelines, automated testing, and infrastructure-as-code for data solutions.
Expected Skills - Data engineering platforms, big data technologies, and cloud-native development (microservices, Kubernetes).
- API design (REST) and integration tools (ETL/ELT).
- Stakeholder communication (technical and non-technical audiences).
- Leadership in Agile/DevOps environments.
- Analytical problem-solving for complex data systems.
- Project management: proficiency in tools like Jira; familiarity with SDLC and CI/CD pipelines.
Expected Knowledge - Foundational Understanding: Data modeling, data pipeline orchestration, data quality management, metadata management, and data lifecycle.
- Data Platforms: Data lakes, warehouses, and lake house architectures; distributed systems and cloud data services.
- Data Engineering: ETL/ELT processes, real-time and batch data processing, data integration, and automation.
- Financial Systems: Payment networks, liquidity management, and settlement processes (as relevant to data flows).
- Regulatory Landscape: Global data privacy regulations (GDPR, CCPA) and compliance tools.
- Security: Data encryption, access controls, and penetration testing methodologies.
Qualifications - Education: Bachelor's/Master's in Computer Science, Engineering, or related field.
- Certifications: AWS/Azure Solutions Architect, Certified Data Engineer, or similar
- Experience: 5 years in solution architecture or technical implementation, with 2 years in data engineering or enterprise data platforms.
- Proficient in system design, integration, and implementation across multiple technology domains.
- Proven track record in deploying scalable financial systems (e.g., payment gateways, digital wallets, stablecoin or cryptocurrency systems preferred)
- Hands-on experience with cloud platforms (Azure/AWS/GCP), containerization (Kubernetes), and DevOps practices.
- Excellent communication, collaboration, and critical thinking skills.
- Understanding of financial regulations, compliance, and security standards.
Expected Deliverables - End-to-end solution architectures for data platforms, including detailed diagrams, technology stack specifications, and integration patterns.
- ETL/ELT pipeline designs and implementation plans for onboarding new data sources and modernizing legacy systems.
- Data governance frameworks, including policies for data quality, lineage, and access control, aligned with Enterprise Architecture standards.
- Technical documentation packages: architecture blueprints, operational runbooks, and security protocols.
- Prototypes and proof-of-concept implementations demonstrating new data engineering capabilities (e.g., streaming analytics, automated data quality checks).
- Performance benchmarks and scalability assessments for deployed solutions.
- Risk mitigation plans, including security audit findings and disaster recovery strategies.
This role combines technical depth with strategic vision to build data platforms that bridge traditional finance and modern analytics ecosystems. The ideal candidate will balance innovation with operational rigor to deliver secure, compliant, and user-centric data solutions. Join M&T Bank and be part of a team that is shaping the future of banking technology.