Jobgether
Senior Data Warehouse Engineer

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This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Warehouse Engineer based in United Kingdom.
As a Senior Data Warehouse Engineer, you will help shape the data backbone that supports a high-scale technology platform and enables smarter business decisions.
You will architect scalable data warehouses, build reliable pipelines, and ensure data remains accurate, accessible, and performant.
The role combines hands-on engineering with close collaboration across data science, analytics, and software engineering teams.
You will work with modern cloud data technologies and optimize warehouse infrastructure for both performance and cost efficiency.
You will also contribute to developer-facing data tools and establish engineering practices that promote clean, well-structured data.
Working within a globally distributed, fully remote environment, you will have significant ownership and autonomy over your work.
This is an opportunity to make a direct impact on data infrastructure while working with modern technologies across cloud, streaming, transformation, and analytics.
Accountabilities
As a Senior Data Warehouse Engineer, you will own key aspects of the data warehouse and pipeline ecosystem, ensuring scalable infrastructure, reliable data flows, and effective collaboration with teams that depend on high-quality data.
- Architect, build, and maintain scalable, high-performance data warehouse solutions that support analytics and operational needs.
- Develop reliable and well-documented data pipelines and ELT processes while maintaining strong standards for data quality and consistency.
- Design and implement efficient data models and transformations using tools such as dbt and SQL.
- Continuously optimize data warehouse performance through query optimization, partitioning, indexing, and other performance-tuning techniques.
- Monitor, troubleshoot, and improve warehouse infrastructure while balancing performance, reliability, and cost efficiency.
- Partner with data analysts and data scientists to transform raw data into actionable insights and support machine learning initiatives.
- Work with modern cloud-based data warehouse technologies, including ClickHouse and other columnar data platforms.
- Integrate data warehouse capabilities seamlessly with application and service infrastructure.
- Contribute to the development of developer-facing data tools that make data more accessible and useful across engineering teams.
- Establish and promote best practices for data engineering, data quality, documentation, testing, and maintainability.
- Apply software engineering principles such as version control, code reviews, testing, and automation to data infrastructure.
- Support data-driven decision-making by ensuring teams have access to clean, reliable, and well-structured information.
- Collaborate effectively across a globally distributed organization and contribute to a strong engineering culture.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Requirements
The ideal candidate is an experienced data engineer who combines strong technical depth in data warehousing and cloud infrastructure with a collaborative, autonomous approach to solving complex problems.
- Extensive experience designing, implementing, and optimizing data warehouses in cloud environments such as AWS or GCP.
- Strong hands-on expertise with data modeling and transformation tools, particularly dbt.
- Excellent SQL skills and experience working with modern columnar data warehouses such as ClickHouse, Databricks, BigQuery, or Snowflake.
- Experience with data pipeline orchestration platforms such as Prefect or Airflow.
- Strong understanding of scalable data pipelines, ELT processes, data quality, and warehouse performance optimization.
- Experience with modern software engineering practices, including version control, code reviews, testing, and automation.
- Familiarity with cloud infrastructure and DevOps practices.
- Experience with infrastructure-as-code tools such as Terraform is a plus.
- Scripting or automation experience with Bash, Python, or Go is a plus.
- Familiarity with business intelligence and visualization tools such as Apache Superset, Sigma, Tableau, or Looker is a plus.
- Ability to work independently, take ownership, and make effective decisions in ambiguous environments.
- Strong collaboration skills and the ability to work effectively with data scientists, analysts, and software engineers.
- Excellent English communication skills for working within a globally distributed team.
- Strong problem-solving mindset and enthusiasm for building scalable, efficient, and maintainable data systems.
- Experience with technologies such as ClickHouse, Redshift, Confluent Kafka, dbt, Prefect, AWS, Terraform, Apache Superset, or Sigma is valuable.
- Must be authorized to work from the location where you reside; visa sponsorship is not available for this position.
- Due to regulatory and security requirements, employment may not be available in certain countries.


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Benefits
- US-based cash compensation of $152,000–$205,000.
- Compensation ranges are benchmarked according to role, level, function, and geographic location.
- Fully remote work within the United States.
- Opportunity to work within a globally distributed, 100% remote organization.
- High level of ownership and autonomy in shaping critical data infrastructure.
- Opportunity to work with modern data warehouse, cloud, streaming, orchestration, and infrastructure technologies.
- Cross-functional collaboration with data scientists, analysts, and software engineers.
- Opportunity to contribute to developer-facing tools and data engineering best practices.
- Inclusive and collaborative working environment that values diverse experiences, perspectives, and backgrounds.
- Professional growth through exposure to large-scale data infrastructure and complex engineering challenges.
- Salary offers may vary based on relevant experience, education, certifications, skills, training, and market conditions.
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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