Senior Big Data Engineer (Python + GCP)

SoftServe; Poland; On-site; USD 120,000 - 160,000; Full time

Job summary

SoftServe is seeking a senior data engineer to design and build scalable data pipelines on Google Cloud Platform. You will work with batch and streaming workloads, leveraging Spark, Databricks, and modern data architectures to unlock data value for clients.

You will collaborate with data scientists, architects, and engineers to translate business needs into robust data solutions, ensure data quality, and support end-to-end deployments on GCP services such as BigQuery, Dataflow, Pub/Sub, and

Qualifications

• 5+ years of professional experience in Big Data or Data Engineering.

Responsibilities

• Design, develop, and maintain scalable data pipelines for batch and streaming workloads
• Build and optimize data processing solutions using Python (must), SQL, Java, Apache Spark, and Databricks
• Create cloud-native data architectures leveraging GCP services including BigQuery, Dataflow, Cloud Composer, Pub/Sub, and Cloud Storage
• Implement data transformation, modeling, and analytics engineering practices using dbt and Dataform
• Collaborate with business stakeholders, architects, and engineering teams to translate data requirements into effective technical solutions
• Support development of modern data platforms and analytics solutions on GCP with GCP native services and/or Databricks
• Contribute to technical design discussions, architecture decisions and continuous improvement initiatives
• Ensure data quality, reliability and performance across data processing workflows
• Support end-to-end project delivery, including PoCs, MVPs, production deployments and platform enhancements

Skills

Python

SQL

Java

Apache Spark

Databricks

GCP (Google Cloud Platform)

Airflow / Cloud Composer

Kafka / Pub/Sub

BigQuery

dbt

Dataform

Data pipelines

Tools

Databricks

Apache Airflow

Cloud Composer

BigQuery

Dataflow

Pub/Sub

Apache Beam

Kafka

dbt

Dataform

Spark

Job description

About The Role

In this role, you will contribute to building scalable and reliable data solutions on Google Cloud Platform, leveraging modern Big Data technologies and cloud-native services. You will work with batch and streaming data processing systems, helping organizations transform, manage, and unlock the value of their data. As part of a collaborative engineering team, you will participate in the full project lifecycle, from discovery and solution design to implementation and production deployment.

About The Role

In this role, you will contribute to building scalable and reliable data solutions on Google Cloud Platform, leveraging modern Big Data technologies and cloud-native services. You will work with batch and streaming data processing systems, helping organizations transform, manage, and unlock the value of their data. As part of a collaborative engineering team, you will participate in the full project lifecycle, from discovery and solution design to implementation and production deployment.

Responsibilities

• Design, develop, and maintain scalable data pipelines for batch and streaming workloads
• Build and optimize data processing solutions using Python (must), SQL, Java, Apache Spark, and Databricks
• Create cloud-native data architectures leveraging GCP services including BigQuery, Dataflow, Cloud Composer, Pub/Sub, and Cloud Storage
• Implement data transformation, modeling, and analytics engineering practices using dbt and Dataform
• Collaborate with business stakeholders, architects, and engineering teams to translate data requirements into effective technical solutions
• Support development of modern data platforms and analytics solutions on GCP with GCP native services and/or Databricks
• Contribute to technical design discussions, architecture decisions and continuous improvement initiatives
• Ensure data quality, reliability and performance across data processing workflows
• Support end-to-end project delivery, including PoCs, MVPs, production deployments and platform enhancements

Requirements

• 5+ years of professional experience in Big Data or Data Engineering
• Advanced expertise in Python and SQL (Java nice to have) for large-scale data processing and transformationHands-on experience developing data solutions on Google Cloud Platform (GCP)
• Experience with Apache Spark and data processing frameworks such as Cloud Dataflow or Apache Beam
• Proven background building scalable solutions using Databricks and Lakehouse concepts
• Experience with orchestration tools such as Apache Airflow or Cloud Composer
• Knowledge of streaming technologies such as Apache Kafka or Google Cloud Pub/Sub
• Strong knowledge of BigQuery and modern cloud data architectures
• Experience with data transformation and modeling tools such as dbt and Dataform
• Strong analytical thinking, troubleshooting capabilities, and problem-solving skills
• Effective communication with both technical and non-technical stakeholders
• Upper-intermediate or higher level of English

SoftServe is an equal opportunity employer. Qualified applicants will receive consideration regardless of race, color, ancestry, ethnicity, national origin, religion, sex, sexual orientation, gender identity or expression, age, citizenship, disability, health condition, marital or family status, veteran status, or any other characteristic protected by applicable law.