Senior Data Engineer: Scalable Pipelines & Data Platforms

Samba; Województwo mazowieckie; On-site; PLN 260,000 - 360,000; Full time

Job summary

Samba seeks an experienced data engineering leader to design and optimize scalable data pipelines powering analytics and insights. You will collaborate with Data Science, Analytics, and Product teams to deliver production-ready data solutions that drive business impact.

The role emphasizes architectural improvements, best practices, and mentoring a team of engineers, with a focus on reliability, performance, and security in cloud data lakes.

Qualifications

• 8+ years of related experience or equivalent practical experience.
• Advanced Python and distributed data processing.
• Expertise with Apache Spark or PySpark and modern data pipelines.

Responsibilities

• Lead architecture and design of scalable, high-performance data pipelines.
• Manage production datasets and versioned outputs for customer-facing reports.
• Govern end-to-end lifecycle of data features with safe rollouts and backfills.
• Engineer cost-aware data ingestion, transformation, and storage solutions.
• Lead incident response and perform root-cause analysis with permanent fixes.
• Improve observability and monitoring of data processes at scale.
• Mentor engineers and advocate best practices in data engineering.

Skills

Python

Distributed data processing

Apache Spark / PySpark

Apache Airflow

Databricks

AWS / GCP

Data modeling

Code quality & testing

Communication

Education

Bachelor's degree

Master's degree

PhD (optional)

Tools

Apache Airflow

Databricks

Apache Spark

PySpark

AWS

GCP

Job description

Samba seeks an experienced data engineering leader to design and optimize scalable data pipelines powering analytics and insights. You will collaborate with Data Science, Analytics, and Product teams to deliver production-ready data solutions that drive business impact.

The role emphasizes architectural improvements, best practices, and mentoring a team of engineers, with a focus on reliability, performance, and security in cloud data lakes.