Senior Data Engineer (Snowflake/Databricks)

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

Salary: $97,100–$161,800 annual USD

Company

M&T Bank is a financial services organization.

What you will do

• Design, develop, test, deploy, and support complex production data pipelines, data products, and data management solutions.
• Build batch, micro-batch, CDC, and streaming pipelines integrating relational, mainframe, API, SaaS, file, object-storage, and event-stream data.
• Implement data solutions across relational databases, cloud object storage, warehouses, and lakehouses using Snowflake, Databricks, dbt, Apache Spark, and comparable technologies.
• Apply data modeling, performance and cost tuning, data quality, reconciliation, metadata, lineage, monitoring, alerting, error recovery, and restartability practices.
• Use Git, peer review, automated testing, CI/CD, technical design reviews, and Agile delivery practices.
• Support production incidents and root-cause analysis, collaborate with architecture, governance, cybersecurity, platform, product, and consuming teams, and mentor less-experienced engineers without direct people-management responsibility.

Requirements

• Associate’s degree with at least 5 years of systems analysis and/or application development experience, or bachelor’s degree with at least 3 years of such experience; alternatively, 7 years of combined education and/or relevant experience including at least 3 years of systems analysis and/or application development.
• Strong SQL skills for complex transformations and analytical queries, plus Python or another general-purpose programming language used for data engineering.
• Hands-on experience with Snowflake, Databricks, or a comparable cloud data platform, and ELT/ETL and transformation practices including dbt or a comparable framework.
• Experience with relational data stores, warehouse or lakehouse data modeling, distributed processing with Apache Spark/PySpark or a comparable framework, and batch processing with knowledge of streaming or event-driven concepts.
• Experience with Git-based source control, automated testing, and CI/CD fundamentals.
• Knowledge of cloud and object-storage concepts, preferably Microsoft Azure; experience with structured and semi-structured formats including Parquet, JSON, CSV, Avro, and XML.
• Experience with Linux/Unix environments and scripting.
• Ability to independently deliver complex pipeline components and data products, troubleshoot production and data-quality issues, apply engineering patterns, communicate risks and dependencies, and manage work from design through production support with limited supervision.

Nice to have

• Production experience with Snowflake, Databricks, Apache Spark/PySpark, and dbt.
• Experience with Apache Iceberg or another open table format, Apache Kafka, CDC, or event-driven processing.
• Experience with Apache Airflow, Azure Data Factory, Databricks Workflows, dbt orchestration, Terraform, or other Infrastructure as Code technology.
• Experience with data catalogs, metadata, lineage, observability, automated data-quality tooling, governed enterprise data products, or regulated financial-services environments.

Culture & Benefits

• Full-time hybrid work arrangement.
• Work is performed within the organization’s risk, regulatory, cybersecurity, governance, and internal-control standards.
• Contribution to an environment that supports belonging and reflects the company brand.
• Compensation is market-informed and determined by the successful candidate’s knowledge, skills, and experience within the stated annual range.