Senior Data Engineer (GCP, Python, SQL, PySpark)

Role: Sr. Data Engineer (GCP, Python, SQL, PySpark)

Work type: Full remote (from Romania)

Collaboration type: employment contract or B2B contract

Role Objective

We are looking for a Senior Data Engineer to design and deliver scalable data pipelines and high-performance analytical solutions using SQL/BigQuery, Spark/PySpark, and Python on Google Cloud. This role focuses on building reliable, cloud-native data products that enable advanced reporting, analytics, and decision-making across the organization.

Key Responsibilities

• Design and implement scalable data pipelines using Azure Fabric

• Design and deliver batch and real-time ETL/ELT pipelines across cloud environments to support analytics and reporting

• Write and optimize advanced SQL transformations and build performant, cost-efficient BigQuery data models

• Implement scalable data processing solutions using Python and PySpark, ensuring maintainable and high-quality code

• Build robust data models and apply validation practices to maintain accuracy and reliability

• Use GCP services such as BigQuery, Dataflow, Cloud Composer, Pub/Sub, and GCS to build and operate modern data platforms

• Troubleshoot complex pipeline issues and continuously improve compute, storage, and processing performance

• Collaborate with engineering, analytics, and business teams while contributing to CI/CD, code reviews, and testing standards

Mandatory Skills

• 5+ years of experience as a Data Engineer, building scalable data pipelines and working with cloud-based data ecosystems

• Expertise in SQL and hands-on experience building performant datasets in BigQuery or similar cloud data warehouses

• Proficiency in Python and PySpark for scalable data processing in distributed environments

• Understanding of data modeling, ELT/ETL patterns, and data quality best practices

• Familiarity with Google Cloud Platform, particularly BigQuery, Dataflow, and Cloud Composer, GCS, or equivalent cloud data services

• Background in building scalable data pipelines, both batch and near real-time, in a cloud-native environment

• Proficiency with version control, CI/CD pipelines, and automated testing frameworks

• Capability to troubleshoot and optimize performance across compute, storage, and processing layers

Nice-to-Have

• Experience with Infrastructure-as-Code, including Terraform, Ansible, and Chef

• Knowledge of shell scripting

• Experience in financial services or regulated environments