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Accenture

Advises businesses and runs their technology

Data Engineer

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

About the Job

Requirements

  • At least 5 years of experience is required.
  • At least 6 years of experience with Databricks Unified Data Analytics Platform is required.
  • 15 years of full-time education is required.
  • Experience with AWS, Azure, or Google Cloud Platform for data engineering workflows.
  • Strong proficiency in PySpark, Spark, or similar frameworks for building scalable data pipelines.
  • Understanding of big data architectures, data storage, and data processing concepts.
  • Familiarity with cloud-native data storage solutions such as Amazon S3, Blob Storage, BigQuery, or Redshift.
  • Experience with data orchestration tools such as Apache Airflow or similar.
  • Knowledge of data formats such as Parquet, Avro, or JSON.
  • Strong coding skills in Python for building data pipelines.
  • Good understanding of SQL and database technologies.
  • Troubleshooting, debugging, and performance optimization skills.
  • Experience with real-time data processing and Kafka or similar tools.
  • Exposure to CI/CD pipelines and DevOps practices in cloud environments.
  • Familiarity with dbt (Data Build Tool) for data transformation workflows.
  • Experience with ETL tools such as Informatica, Talend, or Matillion.

Responsibilities

  • Design, develop, and maintain data solutions for data generation, collection, and processing.
  • Create data pipelines, ensure data quality, and implement extract, transform, and load processes to migrate and deploy data across systems.
  • Assist with the data platform blueprint and design, collaborating with Integration Architects and Data Architects to ensure cohesive integration between systems and data models.
  • Help shape data platform components.
  • Build, maintain, and optimize scalable data pipelines for large-scale data processing as part of the data engineering team.
  • Develop and implement ETL/ELT processes using PySpark, Spark, and other relevant tools to move and transform data from various sources.
  • Assist in designing and deploying solutions in major cloud platforms such as AWS, Azure, or Google Cloud Platform.
  • Support development and maintenance of big data processing frameworks and data lakes for structured and unstructured data.
  • Collaborate with data scientists, analysts, and other engineers to ensure data accuracy and availability.
  • Implement data ingestion strategies for secure and efficient movement of data across storage solutions.
  • Work on real-time streaming data pipelines and batch data processing for high-volume workloads.
  • Develop and maintain reusable code for data extraction, transformation, and loading operations.
  • Contribute to performance tuning of Spark jobs and data pipelines for scalability and efficiency.
  • Assist in maintaining governance and data security practices across cloud 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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