Pay
In line with similar jobs
$97.1K–$162K against $127K–$190K, the middle half of what similar US postings state.
From 2,160 postings in the last year. Stated ranges, not salaries paid.
Senior Data Engineer
Buffalo, NY
Actively hiring, first seen by us 1 day ago- Pay
USD 97,100–161,800/year — pay source
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
Read the full posting- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingDesign, build and support production data pipelines and data products
Build batch, micro-batch, CDC and streaming pipelines with Kafka or similar
Integrate data from relational and mainframe systems, APIs, SaaS and files
Tune SQL, Snowflake and Spark workloads for performance and cost
Participate in production support, incident resolution and root-cause analysis
From the employer’s posting
Design, develop, test, deploy and support complex production data pipelines and data products
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
Tune SQL, Snowflake and Databricks/Spark workloads for performance and cost
Participate in production support, incident resolution and root-cause analysis
Education & alternatives
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.
Posting record
Report an errorActively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 6, 20261 day ago
- Recorded sightings
- 2
- Last seen by us
- Nov 7, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 1
Early. Similar jobs usually come down between day 6 and day 54.
At M&T Bank, jobs usually come down by about day 25.
From 11,508 similar postings that came down, and 81 of M&T Bank’s. Coming down is not always a hire.
M&T Bank is hiring
16 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring at a steady pace
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- Azure
- Databricks
- dbt
- Iceberg
- Kafka
- Snowflake
- Spark
- Terraform
- Airflow
- PySpark
Where the posting names them
- 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.
- 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.
- 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.
- 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.
- 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 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.
- 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.
- 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.
Education and Experience Preferred: - Production experience with Snowflake, Databricks, Apache Spark/PySpark and dbt. - Experience with Apache Iceberg or another open table format.
- 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.
- 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.
- 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.
- 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.
- 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 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 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.
Your next step
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About M&T Bank
- People
- About 194 in 2025.Benefit plan filings (Form 5500)
- Company
- Listed as MTB.
Demand for Data Engineer roles
New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
Job Description Overview:
Primary Responsibilities:
Education and Experience Required:
Education and Experience Preferred:
- 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.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
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
- Location & working pattern
Buffalo, NY
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.