Senior Data Quality Analyst

Wilmington, DE - USA

Monthly Salary: Not Disclosed

Posted on: 3 hours ago

Vacancies: 1 Vacancy

Job Summary

Role - Data Quality Analyst
Location - Buffalo NY Wilmington DE
5 Days Onsite Role

JD

The Senior Data Quality Analyst is a hands-on data quality engineer responsible for building
automation-first controls monitoring and remediation at scale. The 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/GraphQL APIs and
comfortable integrating DQ checks into ETL/ELT CI/CD and event-driven architectures.

POSITION RESPONSIBILITIES:
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/GraphQL/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/ServiceNow) 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 (GitLab 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.

MINIMUM QUALIFICATIONS REQUIRED:
Bachelors 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/GraphQL 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.
IDEAL QUALIFICATIONS PREFERRED
Experience with automated ETL/ELT validation and data integration platforms;
familiarity with pre/post-load checks data contracts and schema enforcement.
Proficiency with DQ/observability platforms (e.g. Informatica Cloud DQ Monte
Carlo Anomalo Collibra OwlDQ) and their SDKs/APIs.
Hands-on data profiling rule design and automated measurement of DQ dimensions
(completeness validity accuracy timeliness uniqueness consistency).
Implemented governance-aligned DQ frameworks (standards metadata contracts
lineage policy as code).
Experience with workflow/automation tools (Power Apps Alteryx or equivalent) and
messaging/queueing for event-driven triage.
Cloud experience (Azure Snowflake): scripting with providers/SDKs secrets
management job orchestration and cost-aware design.
CI/CD in GitLab (or similar): pipeline design automated testing code scanning
environment promotion and approvals.
Exposure to AI/ML-based anomaly detection or statistical monitoring; ability to
integrate model outputs via APIs.
Excellent communication skills-able to explain engineering decisions and automation
tradeoffs to non-technical stakeholders.
Proven ability to manage multiple concurrent automation initiatives and deliver
high-quality solutions on schedule.

Role - Data Quality Analyst Location - Buffalo NY Wilmington DE 5 Days Onsite Role JD The Senior Data Quality Analyst is a hands-on data quality engineer responsible for building automation-first controls monitoring and remediation at scale. The role designs scripts and operationalizes data q...

Role - Data Quality Analyst
Location - Buffalo NY Wilmington DE
5 Days Onsite Role

JD