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About the Role
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.
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.
- 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.
Requirements
- 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.
Skills
- SQL
- Python
- Snowflake
- Databricks
- dbt
- Apache Iceberg
- Apache Kafka
- Git
- CI/CD
- Apache Spark
- PySpark
- Microsoft Azure
- Parquet
- JSON
- CSV
- Avro
- XML
- Linux/Unix
- Apache Airflow
- Azure Data Factory
- Databricks Workflows
- Terraform
- Infrastructure as Code
Location
- Buffalo, New York, United States of America
Work Type
- Onsite
Experience Level
- Minimum of 5 years’ systems analysis and/ or application development work experience (Associate's degree)
- Minimum of 3 years’ systems analysis and/ or application development work experience (Bachelor's degree)
- 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 (In lieu of degree)
Education Level
- Associate's degree
- Bachelor's degree
Salary/Compensations
- $97,100.00 - $161,800.00 Annual (USD)
About the Company
- M&T Bank is committed to fair, competitive, and market-informed pay for our employees.