Data Quality Analyst

NO 3rd Parties or Sponsorship! W2 hourly only!

Duration: through 2026

Onsite 4 days a week

The Senior Data Quality Analyst is a hands‑on data quality engineer responsible for building automation‑first controls, monitoring, and remediation  role designs, scripts, and operationalizes data quality validation pipelines, integrates with observability platforms, and leverages APIs to orchestrate end‑to‑end workflows across cloud and on‑prem environments.

The ideal candidate is fluent in Python and SQL, experienced with REST/Graph

QL APIs, and comfortable integrating DQ checks into ETL/ELT, CI/CD, and event‑driven architectures. This is a role with location options in Buffalo, NY or Wilmington, DE.

• Engineer automated data quality pipelines that detect, diagnose, and remediate data defects; design for scalability, idempotency, and observability.
• Use Python/SQL for data profiling, rule evaluation, schema validation, anomaly detection, and automated exception workflows.
• Implement API-driven integrations (REST/Graph
  
  QL/SDKs) with DQ, catalog, ticketing, notification, and orchestration systems; handle OAuth2, pagination, rate limits, retries, and backoff.
• Define and maintain DQ rule libraries and validation frameworks as reusable, versioned assets; enforce code quality via unit tests, linting, and static analysis.
• Embed automated controls into ETL/ELT and data integration jobs; implement pre/post‑load validations, row/column‑level checks, and SLA/SLO monitoring.
• Build event‑driven alerts and webhook workflows to route exceptions to the right queues (e.g., Jira/Service Now), with metadata for reproducibility and audit.
• Develop KPI dashboards and operations apps using Power BI and Power Apps to visualize coverage, drift, and rule performance, and to streamline triage/remediation.
• Conduct root‑cause analysis using lineage, logs, and metrics; implement automated remediation where feasible (e.g., rollback, quarantine, replay).
• Contribute to CI/CD workflows (Git Lab or equivalent) for DQ assets: automated tests, environment promotion, secrets management, and change controls.
• Author and maintain runbooks, design docs, and operational playbooks; mentor analysts on scripting, APIs, and engineering best practices.
• Uphold risk, regulatory, and internal control requirements; ensure auditability and traceability throughout DQ processes.
• Promote an environment of diversity, equity, inclusion, and alignment with the M&T Bank brand.
• Perform other duties as assigned.

• Bachelor’s degree and a minimum of 5 years related experience; or in lieu of a degree, a combined minimum of 9 years higher education and/or work experience, including a minimum of 5 years related experience.
• Advanced proficiency in Python and SQL for automation, including building reusable libraries, scheduled jobs, and validation pipelines.
• API engineering experience: designing and consuming REST/Graph
  
  QL APIs, handling auth (OAuth2/Bearer), pagination, rate limits, error handling/retries, and webhooks for event‑driven processes.
• Experience building solutions with Power BI and Power Apps for operational reporting and workflow automation.
• Demonstrated success collaborating across engineering, governance, and business teams in fast‑paced environments.