Hybrid Senior Data Engineer Lead Forecasting & ML Platforms

Procter & Gamble; Warszawa; Hybrid; PLN 180,000 - 280,000; Full time

Benefits offered by this job

Private health care

Life insurance

P&G stock options

Saving plans

Lunch subsidy

Sport cards

In-office fitness center

Hybrid work model

Industry certifications

Coaching programs

Job summary

Procter & Gamble in Warsaw is seeking an experienced Senior Data Engineer to lead the Data Engineering horizontal team across forecasting and analytics platforms. You will design, build, and optimize data pipelines, collaborate with data scientists, AI engineers, and DevOps colleagues, and drive data quality across multiple platforms.

The role requires at least 4 years in an engineering position, strong skills in Python, Spark, Databricks, Azure, SQL, Docker, Hive, and CI/CD, plus a Bachelor's

Qualifications

• 4+ years of experience in an engineering role (Data/Software/DevOps).
• Strong data engineering concepts: data model and data pipelines.
• Bachelor’s degree and English proficiency.
• Ability to collaborate in cross-functional teams and lead.

Responsibilities

• Lead a team of Data Engineers (internal and external) and handle technical leadership & people management.
• Design, develop, and implement data solutions to acquire, transform, and optimize data from diverse sources.
• Build scalable data pipelines for efficient processing and analysis.
• Ensure data quality and integrity through validation and cleansing processes.
• Collaborate with Data Scientists, AI engineers, and DevOps in day-to-day tasks.
• Interact with other P&G IT organizations and platform teams.

Skills

Python

Spark

Databricks

Azure

SQL

Docker

Hive

CI/CD

English proficiency

Education

Bachelor's degree

Tools

PyrogAI

Job description

Procter & Gamble in Warsaw is seeking an experienced Senior Data Engineer to lead the Data Engineering horizontal team across forecasting and analytics platforms. You will design, build, and optimize data pipelines, collaborate with data scientists, AI engineers, and DevOps colleagues, and drive data quality across multiple platforms.

The role requires at least 4 years in an engineering position, strong skills in Python, Spark, Databricks, Azure, SQL, Docker, Hive, and CI/CD, plus a Bachelor's