Lead Data Engineer

M&T Bank

. Lead the detailed engineering design, development, testing, deployment and production support of complex data pipelines and reusable data products .

Posted 11/6/2026full-timeBuffalo • New York • United StatesSenior💰 $116,400 - $194,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing complex data pipelines and solutions using advanced SQL, Python, and modern data platforms like Snowflake and Databricks. Proficient in data modeling, performance optimization, and ensuring data quality while adhering to regulatory standards.

Highest-signal resume keywords

Advanced SQL SkillsPython ProgrammingSnowflake EngineeringData Modeling ExperienceCI/CD and Automated Testing

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentData Transformation SolutionsBatch and Streaming ArchitecturesDistributed Data ProcessingData Quality ControlTechnical Design ReviewComplex Data Solutions DeliveryPerformance OptimizationData Modeling ApproachesTroubleshooting Distributed Processing

Soft Skills

Technical LeadershipMentoring EngineersCommunication of Complex Designs

Tools & Technologies

SnowflakeDatabricksApache KafkaDbtGitMicrosoft AzureApache SparkParquetJSONXML

Industry Keywords

Data EngineeringELT/ETL PracticesCloud ComputingRegulatory StandardsData Quality Assurance

Tech Stack

Tools & technologies

ApacheAzureCloudCyber SecurityETLKafkaPySparkPythonSnowflakeSparkSQL

About the role

Key responsibilities & impact

Lead the detailed engineering design, development, testing, deployment and production support of complex data pipelines and reusable data products
Develop maintainable data-processing and transformation solutions using advanced SQL and programming languages such as Python
Engineer solutions using Snowflake, Databricks, dbt and comparable modern data platforms
Design analytical storage solutions using relational databases, cloud object storage, columnar formats and open table formats such as Apache Iceberg
Implement batch, micro-batch, change data capture, event-driven and streaming patterns using technologies such as Apache Kafka
Integrate data from relational and mainframe systems, APIs, event streams, SaaS platforms, files and object storage
Apply normalized, dimensional, denormalized and data-product-oriented modeling approaches
Optimize Snowflake, Databricks/Spark and SQL workloads for performance, scalability, reliability and cost
Build data quality, reconciliation, metadata, lineage, observability, alerting and service-level controls into production solutions
Design for restartability, idempotency, retry, replay, recovery and failure isolation; lead diagnosis and root-cause analysis for complex production incidents
Apply source control, peer review, automated testing, CI/CD, environment promotion and infrastructure/configuration automation
Create reusable libraries, templates, implementation patterns and reference solutions
Evaluate design alternatives and document tradeoffs involving security, privacy, resiliency, maintainability, performance, cost and operational complexity
Contribute to technical standards, identify technical debt and recommend modernization or remediation approaches
Mentor engineers through design reviews, code reviews, pairing and technical problem solving
Partner with product owners, architects, governance, cybersecurity, platform and consuming teams
Develop technical epics and stories, estimate complex work, surface dependencies and risks, and support Agile delivery
Provide technical leadership and mentorship without direct people-management responsibility
Adhere to the Company’s risk and regulatory standards, policies and controls
Design, implement, maintain and enhance internal controls to mitigate risk
Maintain internal control standards, including implementation of audit and regulatory issues
Promote an environment that supports belonging and reflects the Company brand
Complete other related duties as assigned

Requirements

What you’ll need

Associate’s degree and a minimum of 7 years’ systems analysis and/or application development work experience OR Bachelor's degree and a minimum of 5 years’ systems analysis and/or application development work experience
In lieu of a degree, a combined minimum of 9 years’ education and/or relevant work experience, including a minimum of 5 years’ systems analysis and/or application development work experience
Expert proficiency in a minimum of 1 relevant programming language and professional proficiency in a minimum of 1 additional relevant programming language
Advanced SQL skills, including complex transformations, analytical queries and workload optimization
Experience with Python or another general-purpose programming language used for production data engineering
Hands-on engineering experience with Snowflake and/or Databricks
Experience with modern ELT/ETL and transformation practices, including dbt or a comparable framework
Experience with 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 and CI/CD
Experience with batch and streaming architectures, orchestration and production operations
Knowledge of cloud computing and object-storage concepts, preferably in Microsoft Azure
Experience working with structured and semi-structured data using formats such as Parquet, JSON, Avro, CSV and XML
Demonstrated ability to independently design and deliver complex data solutions spanning ingestion, processing, persistence, quality and consumption
Demonstrated ability to troubleshoot complex distributed-processing, data-quality and production reliability issues
Demonstrated ability to balance performance, cost, scalability, resiliency, security and maintainability in technical decisions
Demonstrated ability to review and improve technical designs and code developed by other engineers
Demonstrated ability to communicate complex designs and tradeoffs to engineering, architecture, product and business audiences