data engineer
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Role details
Tech stack
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Job description
We are looking for experienced Data Engineers to join M&T Bankβs data engineering pod, supporting the Finance (Trailblazers) and Fin Crime teams. Today, an IPC job ingests data into Snowflake and performs conversion, ETL, cleansing, validation and address standardization. The pod will keep this pipeline reliable and in production, and will modernize it by migrating the workflows to Butler and SPICE in a medallion architecture (bronze, silver and gold layers). The role suits engineers who are strong in Snowflake and Informatica and are comfortable working with legacy mainframe data, in a regulated banking setting. Engineers will work closely with M&Tβs business and technology teams and be expected to deliver with a high degree of ownership., Support and enhance the IPC job that ingests data into Snowflake, keeping loads reliable, on time and well monitored. Convert source data from EBCDIC to ASCII, handling mainframe file formats and encoding issues accurately. Design, build and maintain ETL workflows that ingest data from source systems into Snowflake. Data quality Cleanse data and apply validation rules using Informatica Data Quality (IDQ), and resolve data quality exceptions. Standardize and validate addresses using Address Doctor (Informatica). Reconcile and test data end to end to confirm accuracy before and after changes. Modernization and migration Analyze the existing workflows and propose a plan to modernize them. Migrate workflows to Butler and SPICE, structured in a medallion architecture (bronze, silver and gold layers). Optimize Snowflake queries, loads and cost, and retire legacy components once migrated. Delivery and operations Troubleshoot job failures, find root causes and put preventive fixes in place. Document data flows, mappings, runbooks and operating procedures. Follow M&Tβs change management, security and data governance standards, and support audit requests. Work with business analysts, data stewards and other engineering teams in Finance and Fin Crime.
Requirements
6+ years of hands-on data engineering and ETL development experience, with strong, recent Snowflake experience (data loading, performance tuning, warehouses, roles and access). Strong SQL, plus scripting in Python or Shell for automation and data processing. Hands-on experience with Informatica for ETL, and with Informatica Data Quality (IDQ) for data cleansing, profiling and validation rules. Experience with address standardization using Address Doctor (Informatica). Experience working with mainframe and legacy data, including EBCDIC to ASCII conversion and fixed-width or copybook-based files. Understanding of medallion architecture (bronze, silver, gold) and experience migrating or re-engineering existing workflows. Experience with job scheduling and orchestration, version control (Git) and CI/CD practices. Ability to troubleshoot production data issues, perform root cause analysis and document solutions. Strong communication skills and the ability to work with business and technology stakeholders.
Preferred Skills Experience in banking, financial services or other regulated environments. Exposure to financial crime data (such as AML or KYC) for the Fin Crime role, or finance and regulatory reporting data for the Finance role. Familiarity with M&Tβs Butler and SPICE frameworks, or similar internal data frameworks. Exposure to AWS or Azure cloud data platforms. Snowflake or Informatica certifications.
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