Jobgether
Data Engineer
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Job Description: Data Engineer
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineer based in United Kingdom.
This role offers the opportunity to build and optimize a modern data platform that powers marketing intelligence, customer insights, and revenue growth across global products. As a Data Engineer, you will design, develop, and maintain scalable data pipelines that transform complex customer data into actionable business value. You will work across the full data lifecycle, from ingestion and transformation to activation and analytics, collaborating with engineering and business teams in a fast-moving technology environment. The position combines hands-on technical challenges with opportunities to influence architecture, data quality, and automation practices. You will use modern cloud technologies and AI-assisted development workflows to create reliable, high-performing data solutions at scale.
Accountabilities
- Build and maintain robust data ingestion pipelines from various sources, including REST APIs, SFTP, and database replication systems into cloud data platforms.
- Develop and optimize data transformation workflows using dbt, following structured bronze, silver, and gold layer modeling practices.
- Design and maintain data models supporting identity resolution, customer segmentation, attribution, and marketing activation use cases.
- Build integrations with external marketing platforms and services, enabling data synchronization, campaign delivery, and feedback collection.
- Develop and manage AWS Lambda functions, Airflow workflows, and orchestration processes to ensure reliable data operations.
- Implement data quality checks, monitoring, alerting, and validation frameworks to maintain accuracy and trust in business-critical datasets.
- Manage cloud infrastructure and data platform components using infrastructure-as-code practices with Terraform.
- Investigate and resolve data incidents, including pipeline failures, quality issues, and sensitive data exposure risks.
- Contribute to continuous improvement of engineering practices, automation, documentation, and scalable data architecture.
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Requirements
- 4+ years of professional experience designing, developing, and deploying production-grade data pipelines using Python.
- Strong expertise in SQL development, including complex queries, optimization techniques, and performance tuning in cloud data environments.
- Hands-on experience with Snowflake, including data loading, external stages, security controls, warehouses, and optimization practices.
- Strong experience with dbt Core for data transformation, testing, incremental models, and analytics engineering workflows.
- Solid understanding of data warehouse design principles, including dimensional modeling, star and snowflake schemas, facts, dimensions, and slowly changing dimensions.
- Experience designing conceptual, logical, and physical data models.
- Proven experience building and operating ETL/ELT pipelines using Airflow or similar orchestration tools.
- Familiarity with modern AI-assisted development workflows and daily use of AI coding tools for development, debugging, and code review.
- Knowledge of AWS services such as S3, Lambda, IAM, and EventBridge, along with Terraform and CI/CD practices.
- Experience with Git, Docker, data quality frameworks, and data lineage practices is highly valued.
- Strong problem-solving skills, attention to detail, and ability to work effectively in a remote, collaborative engineering environment.
- Experience with streaming technologies, marketing platform integrations, or iGaming-related products is considered a plus.
Benefits
- Opportunity to work on scalable, high-impact products within a growing technology environment.
- Fully remote working opportunity across eligible locations.
- Flexible working environment designed to support autonomy and work-life balance.
- Competitive salary package with performance-based incentives.
- Exposure to modern cloud technologies, data architecture patterns, and AI-powered engineering workflows.
- Collaborative and supportive team culture with opportunities for professional growth and technical development.
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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.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
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 and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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