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Accenture

Advises businesses and runs their technology

Data Platform Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • At least 12 years of experience is required.
  • Proven experience designing data engineering workflows and solutions using AWS, Azure, or GCP.
  • Expert-level knowledge of PySpark, Spark, and big data technologies.
  • Extensive experience in data pipeline architecture, design, and optimization.
  • Strong hands-on experience with large-scale ETL/ELT processes and integrating data into cloud-based platforms such as S3, Blob Storage, BigQuery, and Redshift.
  • Proficiency in Python, SQL, and scripting for data pipeline development.
  • Ability to work with real-time data streaming tools such as Kafka and batch processing tools.
  • Experience leading cross-functional teams in implementing cloud-based data platforms and workflows.
  • Solid understanding of data security, compliance, and governance in a cloud environment.
  • 15 years of full-time education is required.

Responsibilities

  • Assist with the data platform blueprint and design, encompassing relevant data platform components.
  • Collaborate with Integration Architects and Data Architects to ensure cohesive integration between systems and data models.
  • Lead the design, development, and optimization of complex data pipelines, ensuring high performance and scalability using PySpark, Spark, and big data technologies.
  • Architect data engineering solutions across AWS, Azure, or GCP to enable secure data ingestion, transformation, and storage.
  • Design and build modular, reusable ETL/ELT pipelines integrating data from various sources into cloud-based data lakes and data warehouses.
  • Collaborate with data scientists, analysts, and engineering teams to develop and maintain large-scale data processing systems.
  • Guide and mentor junior engineers in data engineering, cloud technologies, and big data best practices.
  • Optimize and tune Spark and big data processing jobs to handle high-volume data efficiently and at scale.
  • Enforce data security, privacy, and governance best practices and policies across cloud platforms.
  • Implement automated data testing and monitoring solutions to ensure data quality and pipeline reliability.
  • Drive real-time data processing, batch jobs, and analytics pipelines to support operational and analytical needs.
  • Research new tools and technologies to support continuous improvement in data engineering.

Desired Qualifications

  • Familiarity with dbt for managing data transformation and data quality.
  • Exposure to CI/CD pipelines, DevOps practices, and containerization technologies such as Docker and Kubernetes.
  • Certifications or experience with data tools such as Apache Airflow, Fivetran, Informatica, or Talend.
  • Experience with analytics and business intelligence tools such as Power BI, Tableau, or Looker for visualization over cloud-based data platforms.

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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