Lead Data Engineer

Location: Hybrid position in Buffalo, New York, or Wilmington, Delaware, United States

Salary: $116,400.00–$194,000.00 annual (USD)

Company

M&T Bank is a financial services organization hiring a lead data engineer for enterprise data platforms and governed production solutions.

What you will do

• Lead the design, development, testing, deployment, and production support of complex data pipelines and reusable data products.
• Build batch, micro-batch, CDC, event-driven, and streaming solutions integrating relational and mainframe systems, APIs, SaaS platforms, files, and object storage.
• Engineer warehouse, lakehouse, and analytical storage solutions using Snowflake, Databricks, dbt, relational databases, cloud object storage, columnar formats, and open table formats.
• Implement data quality, reconciliation, metadata, lineage, observability, alerting, service-level controls, restartability, recovery, and failure isolation.
• Optimize data workloads for performance, scalability, reliability, and cost; diagnose complex production incidents and lead root-cause analysis.
• Establish reusable engineering patterns, review designs and code, mentor engineers, contribute to technical standards, and partner with product, architecture, governance, cybersecurity, platform, and consuming teams.

Requirements

• Associate’s degree plus at least 7 years of systems analysis and/or application development experience, or a bachelor’s degree plus at least 5 years of such experience; alternatively, 9 years of combined education and relevant experience, including at least 5 years of systems analysis and/or application development experience.
• Expert proficiency in at least one relevant programming language and professional proficiency in at least one additional relevant programming language.
• Advanced SQL skills, including complex transformations, analytical queries, and workload optimization; production experience with Python or another general-purpose programming language.
• Hands-on experience with Snowflake and/or Databricks, modern ELT/ETL and transformation practices including dbt or a comparable framework, and data modeling for warehouse, lakehouse, and data-product use cases.
• Experience with distributed data processing using Apache Spark/PySpark or a comparable framework.
• Experience with Git-based development, automated testing, code review, CI/CD, batch and streaming architectures, orchestration, and production operations.
• Knowledge of cloud computing and object-storage concepts, preferably Microsoft Azure.
• Experience working with structured and semi-structured data formats including Parquet, JSON, Avro, CSV, and XML.
• Ability to independently deliver complex data solutions spanning ingestion, processing, persistence, quality, and consumption; troubleshoot distributed-processing, data-quality, and production-reliability issues; and balance performance, cost, scalability, resiliency, security, and maintainability.
• Ability to review and improve other engineers’ designs and code and communicate complex designs and tradeoffs to engineering, architecture, product, and business audiences.

Nice to have

• Advanced production experience with Snowflake, Databricks, Apache Spark/PySpark, and dbt.
• Experience with Apache Iceberg or another open table format, including schema evolution, partitioning, snapshots, and table maintenance.
• Experience with Apache Kafka, CDC, event-driven architectures, and orchestration tools such as Apache Airflow, Azure Data Factory, Databricks Workflows, or dbt orchestration.
• Experience with Infrastructure as Code and configuration automation, including Terraform or comparable tooling.
• Experience with data catalogs, metadata management, lineage, data observability, automated data-quality frameworks, governed enterprise data products, or domain-oriented data solutions.
• Experience in a highly regulated environment such as financial services.
• Master’s degree in Computer Science, Engineering, Data Engineering, Information Systems, or a related technical field.

Culture & Benefits

• Hybrid work arrangement in Buffalo, New York, or Wilmington, Delaware.
• Work follows Agile delivery practices with collaboration across product, architecture, governance, cybersecurity, platform, and consuming teams.
• Technical leadership and mentoring are expected without direct people-management responsibility.
• Responsibilities include adherence to risk and regulatory standards, internal controls, audit points, and issues raised by external regulators.