Hybrid Data Engineer — Pipelines, Analytics & APIs (Buffalo)

M&T Bank Corporation; Buffalo (NY); Hybrid; USD 81,000 - 135,000; Full time

Benefits offered by this job

Medical benefits

Retirement plan

Volunteer time off

Job summary

M&T Bank Corporation in Buffalo, NY is seeking a Data Engineer to design, develop, and optimize data pipelines, ETL processes, and analytics solutions for operational reporting, regulatory compliance, and technology decision-making. The role is four days onsite at Seneca One Buffalo, NY with one remote day per week.

You will collaborate with technology management, engineers, and business partners to deliver robust data solutions and improve data quality in a fast-paced financial services

Qualifications

• 5+ years’ higher education and/or work experience in systems design or architecture.
• Experience with Python, SQL, Java or similar languages.
• Experience querying relational databases and understanding ETL processes.

Responsibilities

• Design, develop, maintain, and enhance data pipelines and ETL processes.
• Develop integrations with internal and external data sources via APIs and databases.
• Translate business needs into technical data solutions.
• Create and maintain data models, quality controls, and transformation processes.
• Support dashboards and analytics products using enterprise tools.

Skills

Python

SQL

Java

ETL

Data modeling

Data quality

Cloud basics

Education

Bachelor's degree in Computer Science, Data Analytics, Information Systems, Engineering, Mathematics, or related field

Tools

Power BI

APIs

Databases

Job description

M&T Bank Corporation in Buffalo, NY is seeking a Data Engineer to design, develop, and optimize data pipelines, ETL processes, and analytics solutions for operational reporting, regulatory compliance, and technology decision-making. The role is four days onsite at Seneca One Buffalo, NY with one remote day per week.

You will collaborate with technology management, engineers, and business partners to deliver robust data solutions and improve data quality in a fast-paced financial services