Databricks Data Engineer (ICH Europe)

Accenture Poland; Województwo mazowieckie; Hybrid; PLN 167,400 - 223,200; Full time

Benefits offered by this job

Private medical care

Life insurance

Professional development coaching sessions

Job summary

Accenture Poland is looking for a Data Engineer to design and implement scalable data pipelines using Databricks for various cloud-based environments. The successful candidate will have at least 2 years of experience in data engineering, with skills in SQL, Python, and Spark. This role involves hybrid working conditions, allowing remote work and travel within Europe. Accenture offers comprehensive benefits, including private medical care and professional development opportunities.

Qualifications

• At least 2 years of hands-on experience with SQL, Python or Spark in production.
• Experience designing or implementing ETL/ELT processes using Databricks and Apache Spark.
• Exposure to creating conceptual, logical and physical data models.

Responsibilities

• Design and implement scalable end-to-end data pipelines using Databricks.
• Develop and maintain data models using Lakehouse and Medallion architecture.
• Integrate diverse cloud and enterprise data sources into unified datasets.

Skills

Databricks platform

Apache Spark (PySpark, Spark SQL)

SQL

Data modeling and architecture

CI/CD pipelines

Tools

Databricks Workflows

dbt

MLflow

Job description

Databricks Community of Practice – Poland

We design and build modern data products and advanced GenAI solutions powered by Databricks. Join our team in Warsaw, Kraków, Wrocław, Łódź, and Gdańsk.

Responsibilities

• Design and implement scalable end‑to‑end data pipelines (ETL/ELT) using Databricks, including batch and streaming, and modern orchestration patterns such as Delta Live Tables.
• Develop and maintain data models using Lakehouse and Medallion architecture (Bronze, Silver, 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.

Experience Requirements

• At least 2 years of hands‑on experience with relational or analytical databases, applying SQL, Python or Spark in production.
• At least 1 year of practical experience designing or implementing ETL/ELT processes using Databricks and Apache Spark in cloud‑based environments.
• Exposure to data modelling and architecture: practical experience creating conceptual, logical and physical data models using dimensional, relational or Data Vault techniques.

Technical Skills

• Hands‑on experience with Databricks platform, Delta Lake and Lakehouse architecture.
• Practical knowledge of Apache Spark (PySpark, Spark SQL) for batch and streaming processing.
• Understanding of Medallion architecture design patterns.
• Strong SQL skills in analytical and distributed data environments (e.g., Spark SQL).
• Ability to profile, tune and optimise SQL queries for large‑scale workloads.
• Solid understanding of dimensional modelling.
• Experience building scalable ELT/ETL pipelines in modern cloud‑native environments.
• Experience or interest in processing data on major cloud platforms (GCP, Azure, AWS).
• Familiarity with cloud storage, managed databases and serverless data pipeline services.
• Understanding of CI/CD pipelines and version control (Git).

Nice to Have

• Experience with Databricks Workflows, Unity Catalog, Auto Loader, Structured Streaming.
• Knowledge of streaming technologies such as Kafka.
• Experience with dbt, MLflow, Feature Stores or Infrastructure as Code (e.g., Terraform).
• Exposure to data quality frameworks and monitoring solutions.
• Experience supporting AI/GenAI use cases (LLM data pipelines, vector databases, AI‑ready data preparation).

Programming & Analytics

• Practical scripting or programming skills (SQL, Python, Spark) to support data transformation, automation and basic analytics.
• Ability to translate complex business requirements into robust, scalable data solutions.

Soft Skills & Language

• Strong analytical thinking, problem‑solving and attention to detail.
• Professional working proficiency in English and effective communication with technical and non‑technical stakeholders.
• Willingness to travel to client locations across Europe as required.

Benefits

• Individual support of a People Lead and a specific path of professional development, plus coaching sessions.
• Wide training package: soft, technical and language training, e‑learning platforms, Gallup test, GenAI training, co‑financing courses and certification.
• Employee Assistance Program – legal, financial and psychological consultations.
• Eligibility for the Employee share purchase plan and quarterly dividends.
• Paid employee referral program.
• Private medical care and life insurance.
• Access to the WorkSmile benefits platform and the Multisport card.

Working Conditions

• Employment contract (umowa o pracę).
• Headquarters in Warsaw.
• Hybrid model: remote work, office, and travel to client locations across Europe.

Equal Opportunity Statement

Accenture does not discriminate employment candidates on the basis of race, religion, color, gender, age, disability, national origin, political beliefs, trade union membership, ethnicity, denomination, orientation or any other basis impermissible under Polish law. All our leaders are committed to building a better, stronger and more durable company for future generations.