Senior Data Engineer (AWS to GCP)
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Key skills for this role
About the Role
Jobgether is hiring a Senior Data Engineer for a partner company to lead cloud migration from AWS to GCP and build scalable data pipelines in a media/streaming environment. The role involves designing ETL/ELT workflows, optimizing performance, and collaborating with cross-functional teams.
Key Skills for This Role
Responsibilities
- Design, build, and maintain scalable data pipelines and data products on Google Cloud Platform (GCP)
- Support the migration of existing AWS based data workloads to GCP
- Develop and optimise ETL/ELT workflows using Python, SQL, and PySpark for large scale data processing
- Build, maintain, and enhance data transformations using BigQuery and Dataproc
- Create and manage orchestration workflows using Apache Airflow (Cloud Composer)
- Implement and improve data quality frameworks, ensuring consistency, accuracy, and trust in data outputs
- Collaborate with cross functional teams (analysts, product, engineering) to translate business needs into robust data solutions
- Participate in code reviews, technical discussions, and continuous improvement initiatives
- Contribute to platform reliability, monitoring, documentation, and operational excellence
Requirements
- Strong commercial experience as a Data Engineer working with cloud based data platforms
- Hands on expertise with Google Cloud Platform (GCP), especially BigQuery
- Proven experience building and maintaining Airflow pipelines (Cloud Composer preferred)
- Strong programming skills in Python and solid SQL expertise
- Experience with PySpark and distributed/large scale data processing systems
- Good understanding of data modelling and modern ETL/ELT design patterns
- Experience working with Git based workflows in collaborative engineering environments
- Strong communication skills and ability to work effectively with both technical and non technical stakeholders
- Experience working in Agile delivery environments
Full Job Posting
Role Overview
- You will join a high performing data engineering team building and evolving large scale commercial data products within a dynamic media and streaming environment.
- The role sits at the heart of a major cloud transformation, with key systems being migrated from AWS to Google Cloud Platform (GCP).
- Once the migration is complete, the focus will shift toward optimisation, performance tuning, and delivering new data capabilities that directly support business decision making.
- You will work on end to end data pipelines, modern cloud native architectures, and large scale datasets that power critical analytics and reporting.
- This is a hands on engineering role with strong ownership, where your contributions will have visible impact across multiple business domains.
- You will collaborate closely with analysts, product owners, and engineers in an Agile, fast moving, and collaborative environment.
Accountabilities
- Design, build, and maintain scalable data pipelines and data products on Google Cloud Platform (GCP), ensuring performance, reliability, and scalability.
- Support the migration of existing AWS based data workloads to GCP, ensuring smooth transition and minimal disruption.
- Develop and optimise ETL/ELT workflows using Python, SQL, and PySpark for large scale data processing.
- Build, maintain, and enhance data transformations using BigQuery and Dataproc.
- Create and manage orchestration workflows using Apache Airflow (Cloud Composer).
- Implement and improve data quality frameworks, ensuring consistency, accuracy, and trust in data outputs.
- Collaborate with cross functional teams (analysts, product, engineering) to translate business needs into robust data solutions.
- Participate in code reviews, technical discussions, and continuous improvement initiatives.
- Contribute to platform reliability, monitoring, documentation, and operational excellence.
Requirements
- Strong commercial experience as a Data Engineer working with cloud based data platforms.
- Hands on expertise with Google Cloud Platform (GCP), especially BigQuery.
- Proven experience building and maintaining Airflow pipelines (Cloud Composer preferred).
- Strong programming skills in Python and solid SQL expertise.
- Experience with PySpark and distributed/large scale data processing systems.
- Good understanding of data modelling and modern ETL/ELT design patterns.
- Experience working with Git based workflows in collaborative engineering environments.
- Strong communication skills and ability to work effectively with both technical and non technical stakeholders.
- Experience working in Agile delivery environments.
- Nice to have: experience with Dataproc, Dataplex, Great Expectations or similar data quality tools, AWS services (S3, MWAA, Databricks), and cloud migration projects.
- Exposure to media, streaming, or large scale consumer platforms is a plus.
Benefits
- Competitive compensation aligned with senior level expertise.
- Flexible working arrangements (remote/hybrid depending on team setup).
- Opportunity to work on a large scale cloud migration and modern data platform.
- Career growth through exposure to complex, high impact data products.
- Ongoing training, mentoring, and professional development support.
- Collaborative, Agile working environment that values learning and continuous improvement.
- Opportunity to work on international, large scale datasets and systems.
How Jobgether Works
- We use an AI powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements.
- Our system identifies the top fitting candidates, and this shortlist is then shared directly with the hiring company.
- The final decision and next steps (interviews, assessments) are managed by their internal team.
Data Privacy Notice
- By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer.
- This processing is based on legitimate interest and pre contractual measures under applicable data protection laws (including GDPR).
- You may exercise your rights (access, rectification, erasure, objection) at any time.
- We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses.
- These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans.
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