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TD Bank

Offers banking, loans, and wealth management.

Data Engineer 3

Data EngineeringPosted on Nov 9
Full-timeMt Laurel Township, NJ, USA$98.2k - $159.3k

About the Job

Requirements

  • A degree, postgraduate degree, or technical certificate in Data Management or a related discipline, such as Computer Science or Engineering, or equivalent practical experience.
  • At least 5 years of relevant experience.
  • At least 5 years of experience with Azure Databricks, including designing, developing, optimizing, and supporting notebooks, transformations, and scalable data-processing workloads in enterprise environments.
  • At least 5 years of experience with PySpark, including designing distributed data transformations and processing large-scale datasets using Apache Spark, performance optimization, and troubleshooting.
  • At least 5 years of experience with SQL, including writing, optimizing, and troubleshooting complex queries, transformations, data-validation logic, and performance-intensive workloads.
  • At least 5 years of experience with Azure Data Factory, including designing, developing, scheduling, monitoring, and troubleshooting enterprise-grade ingestion and orchestration pipelines.
  • At least 5 years of experience with big data, ETL, and data engineering, including data-integration patterns, batch and streaming processing, pipeline design, performance, scalability, reliability, and production support.
  • At least 5 years of experience with GitHub or Bitbucket, including source control, branching strategies, pull requests, code reviews, versioning, and collaborative engineering practices.
  • At least 3 years of experience with Delta Lake, including table design, schema management, data versioning, performance optimization, and scalable data operations.
  • At least 3 years of experience with Unity Catalog, including centralized data governance, access controls, metadata management, lineage, and data discovery across Databricks environments.
  • At least 3 years of experience with CI/CD and DevOps practices, including automated build, test, deployment, and promotion processes for data pipelines, notebooks, and related data-engineering components.

Responsibilities

  • Perform data analysis and assess data management requirements for a specific platform or journey, including complex analysis involving multiple pods or products.
  • Maintain expert knowledge of upstream data through data profiling, data quality reporting, and metadata production.
  • Support data acquisition and ingestion.
  • Explain complex, large-scale, and high-impact technical design and development details to non-technical business partners.
  • Elicit, analyze, and understand business and data requirements to develop complete business solutions, including data models, ETL and business rules, data life-cycle management, governance, lineage, and metadata.
  • Ensure data complies with enterprise data standards, policies, and guidelines.
  • Develop and maintain complex data models using industry-standard modeling tools.
  • Develop and maintain complex ETL jobs and frameworks using the bank’s standard tools.
  • Support development and testing teams in resolving data issues, including escalation support on complex issues.
  • Support partners and stakeholders in interpreting and analyzing data.
  • Build working relationships within the pod and across partner teams to support collaboration on pod deliverables.
  • Coordinate with technology work teams, including ITS, ARE, Architecture, and Enterprise Protect, to support delivery.
  • Support the QA team with data analysis and investigations of complex issues and test cases during SIT, UAT, and PAT testing.
  • Provide oversight of post-implementation activities during the warranty period.
  • Execute and approve code check-in and check-out in the source code repository as part of source code management.
  • Work with ITS and ARE teams to support code packaging and deployment through CI and CD into higher environments.
  • Lead participation in application design and architecture reviews.
  • Raise ServiceNow requests and work with the change management team to support release management activities.
  • Lead data engineering initiatives and capabilities, and advance data governance principles across the organization.
  • Ensure metadata and data lineage are captured and compatible with enterprise metadata and data management tools and processes.
  • Follow and contribute to secure coding practices to prevent common coding vulnerabilities.
  • Identify and document technical decisions, risks, and lessons learned, and implement corresponding enhancements.
  • Protect organizational interests by identifying and managing risks and escalating non-standard, high-risk activities as necessary.
  • Follow internal policies, procedures, and applicable regulatory guidelines.
  • Keep current with emerging trends and developments and grow knowledge of the business, tools, and techniques.
  • Enable team members by sharing knowledge and engineering best practices.
  • Participate as a team member, support a positive work environment, and communicate issues and relevant information in a timely manner.
  • Provide thought leadership or industry knowledge on data engineering best practices and participate in knowledge transfer within the team and business unit.
  • Participate in personal performance management and development activities, including cross-training within the team.
  • Keep others informed about project status, progress, and relevant day-to-day information.
  • Mentor and enable team members by sharing knowledge and engineering best practices.
  • Support the team by providing guidance and proactively identifying and resolving issues.
  • Develop productive working relationships with internal and external business partners and stakeholders.
  • Contribute to a fair, positive, and equitable environment that supports a diverse workforce.
  • Represent the business area and bank as a brand ambassador internally and externally.

Desired Qualifications

  • A graduate degree is preferred.
  • At least 5 years of experience with analytical and problem-solving work, including investigating complex data and application issues, conducting root-cause analysis, evaluating solution options, and implementing sustainable solutions.

About the Company

TD Bank

Offers banking, loans, and wealth management.

TD Bank provides a wide range of banking and financial services in North America for individuals, businesses, and corporations. Core offerings include checking and savings accounts, credit cards, loans, mortgages, investment products, and wealth management. TD Bank emphasizes digital banking through online and mobile apps that let customers manage money, pay bills, deposit checks, transfer funds, and manage cards. Revenue comes from interest on loans, service fees, and investment income. The company differentiates itself with a broad product lineup, large North American footprint, and integrated services for both personal and business customers, plus a focus on digital accessibility. Its goal is to be a leading, accessible financial institution that helps customers manage and grow their money through convenient, everyday banking and investment solutions.

Company size
10,001+
Company stage
IPO
Headquarters
Toronto, Canada
Founded
1955

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