Senior Python Data Engineer, Azure & Spark (Remote)

4901 Accenture Services Sp.zoo Company; Wrocław; Hybrid; PLN 260,000 - 380,000; Full time

Benefits offered by this job

Permanent contract or B2B

Private medical care

Life insurance

Employee referral program

MyBenefit & Multisport

Job summary

Accenture is hiring a senior data & software engineer to design cloud-based data solutions for risk and margining within Prime Brokerage. You will build ETL pipelines with Python and PySpark, and develop Azure-based data platforms using Databricks and ADLS, while contributing to CI/CD in Unix environments.

Demonstrated experience in SDLC within Agile delivery, strong English communication, and a track record of transforming requirements into scalable data solutions is required.

Qualifications

• 10+ years of professional software and data engineering experience.
• Strong Python and PySpark development, recent hands-on use.
• Experience with Java and/or C# and ETL/data processing design.
• Unix/Linux expertise, file ops, permissions and scripting.
• GitLab CI/CD, Agile SDLC and Azure data services knowledge.

Responsibilities

• Design and develop cloud-based data solutions for risk and margining domains.
• Build and optimize ETL pipelines with Python and PySpark.
• Develop Azure-based data platforms using Databricks and ADLS.
• Contribute to CI/CD, agile delivery, and coding standards.

Skills

Python

PySpark

Java

C#

Unix/Linux

Shell scripting

GitLab CI/CD

Azure Databricks

Azure Data Lake Storage

English communication

Tools

GitLab

Databricks

Azure

Unix/Linux

Shell scripting

Autosys

Oracle databases

Job description

Accenture is hiring a senior data & software engineer to design cloud-based data solutions for risk and margining within Prime Brokerage. You will build ETL pipelines with Python and PySpark, and develop Azure-based data platforms using Databricks and ADLS, while contributing to CI/CD in Unix environments.

Demonstrated experience in SDLC within Agile delivery, strong English communication, and a track record of transforming requirements into scalable data solutions is required.