Manager, Data Quality Engineering

Scotiabank; Dallas (TX); On-site; USD 140,000 - 180,000; Full time

Benefits offered by this job

Flexible benefits

Career development

Job summary

Scotiabank is seeking a Manager, Data Quality Engineering to lead hands-on engineering and people leadership, building scalable quality controls on a modern Lakehouse platform. You’ll drive profiling, rule management, anomaly detection, and data observability across pipelines and data products.

In this role you will partner with the Head and VP of Data Management Engineering to implement measurable quality controls, collaborate with risk stakeholders, and promote reusable data quality patterns

Qualifications

• Bachelor's degree required in a relevant field.
• 7+ years of data engineering or data quality experience with 5+ years in leadership.
• Experience in regulated industries and regulatory reporting is a plus.

Responsibilities

• Design, build, and scale enterprise data quality capabilities on Lakehouse platforms.
• Embed automated quality checks into end-to-end data pipelines and data products.
• Develop data quality scorecards, observability, incident management, and evidence capture.
• Partner with data owners, engineers, and risk teams to define quality expectations.
• Productize data quality capabilities as reusable services and templates.
• Lead root-cause analysis and continuous improvement for data quality issues.

Education

Bachelor's degree in computer science, engineering, information technology, data management, or a related discipline

Tools

Databricks

Delta Lake

Unity Catalog

Lakehouse

Data quality platforms

Profiling tools

Observability frameworks

Rule engines

Monitoring capabilities

Metadata-driven controls

Catalog integration

Data contracts

Azure cloud

Job description

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Title: Manager, Data Quality Engineering

Requisition ID: 271992

Salary Range:-

Please note that the Salary Range shown is a guideline only. Salary offered may vary based on factors, including, but not limited to, the successful candidate’s relevant knowledge, skills, and experience.

Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.

Global Banking and Markets Global Banking and Markets (GBM) is a leading Canadian Capital Markets and Investment Banking business with a growing platform in the US and Latin America, operating globally for over 100 years. Scotiabank’s strong U.S. presence provides our clients an important bridge to this key global market for trade and investment flows across the Americas and the world. Global Banking & Markets provides a full range of investment banking, credit and risk management products and services relevant to the financing and strategic development needs of our clients. Our products include debt and equity financing, mergers & acquisitions, corporate banking, institutional equity sales, trading and research, fixed income products, derivatives, energy, foreign exchange and precious & metals. We also cross-sell the full range of wholesale products and services offered by the Scotiabank Group. Be part of an innovative, Global Capital Markets and Investment Banking business with a unique geographic footprint that puts capital to work for our clients across industries! We work together to drive ambition for every future!

Purpose

The Manager, Data Quality Engineering, is a hands-on engineering people leader responsible for designing, building, and scaling enterprise data quality capabilities on a modern Databricks Lakehouse platform. This role is critical to strengthening trust in data by embedding automated quality controls, observability, and remediation workflows across data pipelines, data products, and regulatory reporting processes.

You will partner with the Head and VP of Data Management Engineering to drive execution and adoption of enterprise data quality capabilities, including profiling, rule management, anomaly detection, quality scorecards, data observability, incident management, and quality controls integrated directly into Lakehouse engineering workflows.

What You'll Do

Data Quality Strategy & Engineering Execution

• Deliver the enterprise data quality engineering solution aligned to Lakehouse architecture, including Databricks, Delta Lake, Unity Catalog, and the Enterprise Data Catalog.
• Establish scalable data quality capabilities for:
  • Data profiling, quality rule authoring, and rules lifecycle management
  • Completeness, accuracy, validity, uniqueness, timeliness, consistency, and freshness checks
  • Quality thresholds, SLOs, scorecards, and certification criteria for critical data assets
  • Data quality issue detection, triage, ownership, remediation, and evidence capture
• Embed automated quality checks into end-to-end data pipelines, including Bronze, Silver, and Gold layers, so issues are detected early and prevented from flowing downstream.
• Partner with data owners, stewards, engineers, platform teams, and risk stakeholders to define quality expectations for critical data elements and data products.
• Drive adoption of reusable data quality patterns, templates, and APIs that make quality controls easy for engineering teams to implement at scale.
• Ensure data quality controls are measurable, auditable, and aligned with regulatory, reporting, and operational risk requirements.

Data Observability, Monitoring & Trust

• Build and operate data observability capabilities that provide visibility into freshness, volume, schema drift, distribution changes, completeness, and reliability across critical pipelines.
• Implement automated profiling, anomaly detection, alerting, and monitoring to identify quality issues before they impact analytics, AI, reporting, or downstream business processes.
• Create quality dashboards, scorecards, and service-level indicators that help business and technology stakeholders understand data health, trends, and risk exposure.
• Lead root-cause analysis and continuous improvement efforts for recurring data quality issues, partnering with source system, pipeline, and product teams to eliminate defects at the source.

Data Quality Productization & Adoption

• Productize data quality capabilities as reusable platform services, including rule libraries, validation templates, metadata-driven controls, and self-service onboarding patterns.
• Ensure data contracts include explicit quality expectations such as schema, SLA/SLO, freshness, completeness, and acceptance criteria.
• Promote trusted, certified, and fit-for-purpose data assets by integrating quality signals into catalog, marketplace, and stewardship workflows.

What You'll Bring

• Bachelor's degree in computer science, engineering, information technology, data management, or a related discipline.
• 7+ years of experience in data engineering, data quality, data management, or platform engineering, with 5+ years in a people leadership role.
• Experience in financial services or other highly regulated industries, including familiarity with auditability, controls, regulatory reporting, and operational risk expectations.
• Hands-on experience with:
  • Databricks, Delta Lake, Unity Catalog, workflows, and Lakehouse data engineering patterns
  • Data quality platforms, profiling tools, observability frameworks, rule engines, and monitoring capabilities
  • Metadata-driven controls, catalog integration, lineage-aware quality monitoring, and data contract implementation
  • Strong understanding of data quality dimensions, critical data elements, quality scorecards, SLAs/SLOs, and issue management workflows
  • Practical experience embedding quality controls into batch, streaming, and orchestration workflows
  • Cloud platform experience, with Azure preferred
• Deep expertise in data quality engineering, observability, profiling, rule management, monitoring, and remediation at enterprise scale.
• Strong understanding of data governance, metadata, lineage, security, privacy, and regulatory compliance as they relate to data quality controls.
• Proven ability to work directly with engineers, data engineers, architects, data owners, stewards, and risk partners to deliver measurable improvements in data trust.
• Exceptional written communication skills with strong attention to technical accuracy, operational discipline, and executive-ready reporting.

What's in it for you?

Scotiabank wants you to be able to bring your best self to work – and life, every day. With a focus on holistic well-being, our many flexible benefit programs are designed to help support your unique family, financial, physical, mental, and social health needs.

#Dallas

Scotiabank is a leading bank in the Americas. Guided by our purpose: "for every future", we help our customers, their families and their communities achieve success through a broad range of advice, products and services, including personal and commercial banking, wealth management and private banking, corporate and investment banking, and capital markets.

At Scotiabank, we value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone. If you require accommodation (including, but not limited to, an accessible interview site, alternate format documents, ASL Interpreter, or Assistive Technology) during the recruitment and selection process, please let our Recruitment team know.

Scotiabank is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by federal, state, or local law.

Nearest Major Market: Dallas

Nearest Secondary Market: Fort Worth

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