Senior Data Engineer: Scalable Pipelines & Data Products

M&T Bank; Wilmington (DE); On-site; USD 116,000 - 194,000; Full time

Job summary

M&T Bank is seeking an experienced data engineer to design, build and operate scalable data pipelines and data products across cloud, warehouse and lakehouse platforms. You will collaborate with product, governance and cybersecurity teams to deliver observable, cost-efficient solutions.

The role requires advanced SQL and Python skills, hands-on Snowflake/Databricks experience, and strong data-modeling capabilities.

Qualifications

• Associate degree with 7+ years of systems analysis/application development, or Bachelor's with 5+ years (9 years total optional).
• Expert in at least one programming language and professional proficiency in another.
• Advanced SQL skills with complex transformations and workload optimization.
• Experience with Python or another general-purpose language for production data engineering.
• Hands-on experience with Snowflake and/or Databricks.
• Experience with modern ELT/ETL and transformation practices (dbt or similar).
• Experience with data modeling for warehouse, lakehouse and data-product use cases.
• Experience with distributed processing (Spark/PySpark) and Git-based development with CI/CD.
• Knowledge of cloud and object-storage concepts (Azure preferred).
• Experience with structured/semi-structured data formats (Parquet, JSON, Avro, CSV, XML).
• Ability to design and deliver complex data solutions across ingestion, processing, persistence, quality and consumption.
• Ability to troubleshoot distributed data quality and production reliability issues.
• Ability to balance performance, cost, resiliency, security and maintainability.

Responsibilities

• Lead design, development, testing, deployment and production support of complex data pipelines and reusable data products.
• Develop maintainable data-processing solutions using SQL and Python.
• Engineer solutions on Snowflake, Databricks and similar platforms and choose appropriate patterns.
• Design analytical storage using relational databases and cloud storage formats.
• Implement batch, micro-batch, CDC and streaming patterns using Kafka or similar platforms.
• Integrate data from multiple sources with appropriate security controls.
• Apply data modeling approaches based on access and lifecycle requirements.
• Optimize Snowflake/Databricks/Spark workloads for performance and cost.
• Build data quality, lineage, observability and SLAs into production solutions.
• Design for restartability and idempotency; lead root-cause analysis for incidents.
• Apply CI/CD and infrastructure automation to data engineering delivery.
• Create reusable libraries, templates and reference solutions.
• Document tradeoffs on security, privacy, resiliency and maintainability.
• Mentor engineers and collaborate across product/governance teams.
• Develop epics/stories and support iterative delivery in Agile environments.

Skills

SQL

Python

Data Modeling

Snowflake

Databricks

dbt

Spark/PySpark

Git

CI/CD

ETL/ELT

Airflow

Kafka

Azure

Parquet/JSON

Education

Bachelor's degree in Computer Science, Engineering or related field

Advanced degree preferred

Tools

Snowflake

Databricks

dbt

Apache Spark/PySpark

Airflow

Terraform

Azure

Job description

M&T Bank is seeking an experienced data engineer to design, build and operate scalable data pipelines and data products across cloud, warehouse and lakehouse platforms. You will collaborate with product, governance and cybersecurity teams to deliver observable, cost-efficient solutions.

The role requires advanced SQL and Python skills, hands-on Snowflake/Databricks experience, and strong data-modeling capabilities.