Senior Data Engineer

Job Description Overview: - Designs, develops, tests, deploys and supports complex data pipelines, data products and data management solutions across modern cloud, warehouse and lakehouse platforms. Applies software-engineering, data-modeling and distributed-processing practices to deliver secure, reliable, maintainable and cost-conscious solutions. Works independently on defined outcomes, collaborates across technology and data teams, and contributes to reusable engineering patterns and continuous improvement. Primary Responsibilities: - Design, develop, test, deploy and support complex production data pipelines and data products with guidance on broader architecture where needed. - Develop maintainable data-processing and transformation solutions using SQL and programming languages such as Python. - Implement solutions using Snowflake, Databricks, dbt and comparable modern data platforms and frameworks. - Build data solutions across relational databases, cloud object storage, warehouse and lakehouse architectures, including open table formats such as Apache Iceberg where applicable. - Develop batch, micro-batch, CDC and streaming pipelines using approved enterprise patterns and technologies such as Apache Kafka or comparable platforms. - Integrate data from relational and mainframe systems, APIs, event streams, SaaS platforms, files and object storage. - Apply normalized, dimensional and denormalized data-modeling techniques appropriate to analytical and data-product requirements. - Tune SQL, Snowflake and Databricks/Spark workloads for performance and cost using appropriate partitioning, parallelism and compute practices. - Implement data quality, reconciliation, metadata, lineage, logging, monitoring and alerting controls. - Build pipelines that support error handling, restartability, idempotency, retry, replay and recovery using established patterns. - Participate in production support, incident resolution and root-cause analysis; implement corrective actions to prevent recurrence. - Use Git, peer review, automated testing, CI/CD and environment promotion practices for data engineering delivery. - Develop and reuse shared components, templates and patterns; contribute improvements to engineering standards and documentation. - Participate in technical design and code reviews, identify implementation risks and escalate architectural concerns appropriately. - Partner with product owners, architects, governance, cybersecurity, platform and consuming teams to clarify requirements and deliver supported solutions. - Contribute to technical epics and stories, estimate assigned work, identify dependencies and deliver through Agile practices. - Provide day-to-day technical assistance and informal mentoring to less-experienced engineers. This role does not have direct people-management responsibility. - Understand and adhere to the Company’s risk and regulatory standards, policies and controls in accordance with the Company’s Risk Appetite. - Design, implement, maintain and enhance internal controls to mitigate risk on an ongoing basis. Identify risk-related issues requiring escalation to management. - Maintain internal control standards, including timely implementation of internal and external audit points and issues raised by external regulators, as applicable. - Promote an environment that supports belonging and reflects the Company brand. - Complete other related duties as assigned. Education and Experience Required: - Associate’s degree and a minimum of 5 years’ systems analysis and/ or application development work experience or Bachelor's degree and a minimum of 3 years’ systems analysis and/ or application development work experience. In lieu of degree, a combined minimum of 7 years’ education and/or relevant work experience, including a minimum of 3 years’ systems analysis and/or application development work experience - Strong SQL skills, including development of complex transformations and analytical queries. - Experience with Python or another general-purpose programming language used for data engineering. - Hands-on experience with Snowflake, Databricks or a comparable cloud data platform. - Experience with ELT/ETL and transformation practices, including dbt or a comparable framework. - Experience with relational data stores and warehouse or lakehouse data-modeling concepts. - Experience with distributed processing using Apache Spark/PySpark or a comparable framework. - Experience with Git-based source control, automated testing and CI/CD fundamentals. - Experience with batch data processing and working knowledge of streaming or event-driven concepts. - Knowledge of cloud and object-storage concepts, preferably in Microsoft Azure. - Experience working with structured and semi-structured data using formats such as Parquet, JSON, CSV, Avro and XML. - Experience with Linux/Unix environments and scripting. - Demonstrated ability to independently deliver complex data pipeline components and data products within an established architecture. - Demonstrated ability to troubleshoot data-processing, data-quality and production issues across multiple technologies. - Demonstrated ability to apply established engineering patterns while identifying opportunities for improvement. - Demonstrated ability to communicate implementation choices, risks and dependencies to technical and product partners. - Demonstrated ability to manage assigned work from design through production support with limited day-to-day supervision. Education and Experience Preferred: - Production experience with Snowflake, Databricks, Apache Spark/PySpark and dbt. - Experience with Apache Iceberg or another open table format. - Experience with Apache Kafka, CDC or event-driven data processing. - Experience with orchestration technologies such as Apache Airflow, Azure Data Factory, Databricks Workflows or dbt orchestration. - Experience with Terraform or another Infrastructure as Code technology. - Experience with data catalogs, metadata, lineage, observability or automated data-quality tooling. - Experience delivering governed enterprise data products. - Experience working in a regulated environment such as financial services. M&T Bank is committed to fair, competitive, and market-informed pay for our employees. The pay range for this position is $97,100.00 - $161,800.00 Annual (USD). The successful candidate’s particular combination of knowledge, skills, and experience will inform their specific compensation. Location Buffalo, New York, United States of America