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Open nowPosted today

Senior Data Engineer

M&T Bank725 open roles

Pay
$97,100 – $161,800 a year
Where
Buffalo NY
Work mode
Hybrid
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Your applicationOpen nowSenior Data EngineerM&T Bank · Buffalo NY

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The clock on this job

Early applications get read.

13.5% of postings close within 7 days. Measured by our own scanner across the market. M&T Bank postings stay open a median of 35 days.

Share of postings closed within
  1. 2.3%1 day
  2. 4.6%3 days
  3. 13.5%7 days
  4. 21.8%14 days
  5. 36.6%30 days
  6. 58.9%60 days
This job: posted today

M&T Bank median: 35 days open

The posting

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

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