2 months ago
Warsaw, Poland or Kraków, PolandMid Level
Responsibilities
- Design and implement scalable end-to-end batch and streaming ETL/ELT pipelines using Databricks and Delta Live Tables.
- Develop and maintain Lakehouse and Medallion architecture data models across Bronze, Silver, and Gold layers.
- Build data transformations with PySpark, Spark SQL, and Delta Lake.
- Integrate 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 version control, CI/CD pipelines, and data workflow testing.
- Profile, tune, and optimize SQL queries and support data transformation, automation, and basic analytics.
- Translate complex business requirements into robust, scalable data solutions.
- Travel to client locations across Europe and beyond as required.
Requirements
- At least 2 years of hands-on experience with relational or analytical databases, SQL, Python, or Spark in production environments.
- At least 1 year of practical experience designing or implementing Databricks and Apache Spark ETL/ELT processes in cloud-based environments.
- Practical experience creating conceptual, logical, and physical data models using dimensional, relational, or Data Vault techniques.
- Hands-on experience with Databricks, Delta Lake, Lakehouse architecture, Apache Spark, PySpark, and Spark SQL.
- Strong SQL skills in analytical and distributed data environments, including query profiling and optimization.
- Experience building scalable ELT/ETL pipelines in modern cloud-native environments.
- Experience with or strong interest in GCP, Azure, or AWS data processing and integration.
- Understanding of CI/CD pipelines and Git-based version control in data engineering projects.
- Professional working proficiency in English and effective communication with technical and non-technical stakeholders.
- Willingness and ability to work at client locations, primarily across Europe, and travel as required.
- Preferred experience includes Databricks Workflows, Unity Catalog, Auto Loader, Structured Streaming, Kafka, dbt, MLflow, Feature Stores, Terraform, data quality frameworks, monitoring solutions, and AI/GenAI data use cases.
Benefits
- Individual support from a People Lead, professional development planning, and access to coaching.
- Soft, technical, language, GenAI, e-learning, certification, and course co-financing opportunities.
- Employee Assistance Program with legal, financial, and psychological consultations.
- Employee share purchase plan eligibility and quarterly dividends for eligible employees who own company shares.
- Paid employee referral program.
- Private medical care and life insurance.
- Access to the WorkSmile benefits platform, including products and services such as a Multisport card.
- Employment contract in Poland with headquarters in Warsaw.
- Hybrid work model combining remote work, Accenture office work, and client-site work depending on project circumstances, with required in-person collaboration and travel to client locations across Europe and beyond.
Tech Stack
Apache KafkaApache SparkAWSAzureDatabricksdbtGitGoogle CloudGoogle Cloud PlatformMLflowPythonSQLTerraform
Categories
Data Engineering
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.