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Accenture

Advises businesses and runs their technology

Databricks Data Engineer

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

About the Job

Requirements

  • At least 2 years of hands-on experience with relational or analytical databases, applying SQL, Python, or Spark for development, testing, debugging, and performance optimization in production environments.
  • Within that experience, at least 1 year of practical experience designing or implementing ETL/ELT processes using Databricks and Apache Spark in cloud-based environments.
  • Practical experience creating conceptual, logical, and physical data models using dimensional, relational, or Data Vault techniques in analytical environments.
  • Hands-on experience with the Databricks platform, including Delta Lake and Lakehouse architecture concepts.
  • Practical knowledge of Apache Spark (PySpark and Spark SQL), including batch and streaming processing.
  • Understanding of Medallion architecture design patterns.
  • Strong hands-on SQL skills in analytical and distributed data environments, such as Spark SQL.
  • Ability to profile, tune, and optimize SQL queries for large-scale data-processing workloads.
  • Solid understanding of dimensional modelling and ability to translate business requirements into conceptual, logical, and physical models.
  • Hands-on experience building scalable ELT/ETL pipelines in modern cloud-native environments.
  • Experience with, or strong interest in, processing and integrating data on major cloud platforms (GCP, Azure, or AWS).
  • Understanding of CI/CD pipelines and version control (Git) in data engineering projects.
  • Practical scripting or programming skills in SQL, Python, or Spark to support data transformation, automation, and basic analytics.
  • Professional working proficiency in English.
  • Willingness and ability to travel to client locations across Europe and beyond, for short or long terms, as required.

Responsibilities

  • Design and implement scalable end-to-end data pipelines (ETL/ELT) using Databricks for batch and streaming, including orchestration patterns such as Delta Live Tables.
  • Develop and maintain data models using Lakehouse and Medallion architecture (Bronze, Silver, and Gold layers).
  • Build robust data transformations using PySpark, Spark SQL, and Delta Lake.
  • Integrate diverse cloud and enterprise data sources into unified, high-quality, analytics-ready datasets.
  • Collaborate with architects, analysts, and data scientists to deliver production-grade data products.
  • Implement DevOps and DataOps practices, including Git-based version control, CI/CD pipelines, and testing of data workflows.
  • Translate complex business requirements into robust, scalable data solutions.

Desired Qualifications

  • Familiarity with cloud storage, managed databases, and serverless or data-pipeline services.
  • Experience with Databricks Workflows, Unity Catalog, Auto Loader, or Structured Streaming.
  • Knowledge of streaming technologies such as Kafka.
  • Experience with dbt, MLflow, Feature Stores, or Infrastructure as Code such as Terraform.
  • Exposure to data-quality frameworks and monitoring solutions.
  • Experience supporting AI/GenAI use cases, such as LLM data pipelines, vector databases, or AI-ready data preparation.

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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