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Accenture

Advises businesses and runs their technology

Data Migration/ Modernization Lead

Data EngineeringConfirmed live in the last 24 hours
Full-timeCA$108.8k - CA$220.4k /yr

About the Job

Requirements

  • A minimum of 8 years of experience implementing data architecture and solutions is required.
  • A minimum of 5 years of experience delivering and implementing Data & Analytics solutions on Azure, AWS, Google Cloud, or on-premises infrastructure using appropriate services to deliver client value is required.
  • Experience as a Data Consultant in solutioning and building scalable data platforms is required.
  • Experience with Microsoft Fabric Data Factory, PySpark, Spark SQL, Delta Lake, Azure Data Factory, Azure Storage, Spark Structured Streaming, and Kafka or Azure Event Hub is required.
  • Experience with Microsoft Purview, Fabric RTI, Azure infrastructure (SHIR, VNET), Azure DevOps, Git, CI/CD, and Azure Functions is required.
  • A bachelor's degree or completion of a college program in computer science or a related field is required.
  • Eligibility for Canadian Secret Clearance is required.
  • English is required because the role regularly interacts with English-speaking stakeholders across Canada, the US, and other countries; the company cannot reorganize its activities to avoid this requirement.
  • Advanced proficiency in data engineering and pipeline implementation is required.

Responsibilities

  • Lead the technology solution, architecture, and delivery of large or complex full-lifecycle data applications across cloud, hybrid, and on-premises environments.
  • Design and build robust data pipelines using scalable architecture, tools, and techniques to produce high-quality data structures.
  • Design data solutions, architect data transformation projects, develop solution blueprints and data modernization or migration plans, and document and present recommendations to clients or stakeholders.
  • Implement faster data-processing methods and integrate complex business logic compatible with daily or real-time streaming frameworks.
  • Automate and scale complex data sets based on customer analytics use cases, including structured data delivery for business analysis, daily extraction of mission-enabling data for data mining or exploration, and transforming data for applied intelligence and data visualizations.
  • Drive business and proactive development activities such as proposal responses and recruitment.
  • Stand up the platform’s data services and streaming components, and demonstrate that data can be ingested, processed, and consumed to meet business needs.
  • Deploy and configure database, streaming, and processing components, and build ingestion and transformation pipelines from priority data sources to curated datasets for analytical consumption.
  • Implement data-quality validation, register metadata and lineage in the catalogue, and enable analyst and data-science access to curated data.
  • Collaborate with Platform and DevOps consultants to deploy data components using the same infrastructure-as-code and pipeline discipline as the rest of the platform.
  • Collaborate with the Lead Enterprise Architect on data modelling and ontology for the priority domain.
  • Build scheduled and event-driven ingestion pipelines, including change data capture where required.
  • Develop transformation logic and business rules to curate raw data into consumable datasets.
  • Implement data-quality rules and automated validation across the pipeline.
  • Establish metadata, lineage, and access registration.
  • Develop strategies, solutions, and processes for managing enterprise-wide data throughout the data life cycle.

Desired Qualifications

  • Advanced proficiency in streaming data architecture is recommended.
  • Production implementation experience for all listed qualifications is desirable.
  • Production experience building real-time analytics applications is desirable.
  • Experience with both batch and stream-processing technologies is desirable.
  • Machine-learning experience with Spark or similar technology is desirable.
  • Experience with another cloud service provider, such as Oracle or Informatica, or with open-source technologies such as Spark, Kafka, Presto, Hive, or Cassandra is desirable.
  • Certification as a Data Solution Architect in one or more cloud technologies, such as AWS, GCP, or Azure, is desirable.
  • Ability to manage numerous requests concurrently and prioritize and deliver is desirable.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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