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Senior Data Engineer (Python/Tableau)
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDevelop and optimize complex SQL transformations for analytics and reporting
Design and extend enterprise data models (Data Vault, dimensional, 3NF)
Build and run SQL-centric ETL/ELT pipelines with monitoring and stability
Implement data quality checks and SQL testing frameworks
Use Python for automation and API integrations
From the employer’s posting
Develop and optimize complex SQL transformations to support analytics and reporting
Design and extend enterprise data models (Data Vault, dimensional, 3NF) and maintain standards
Build and operate SQL-centric ETL/ELT pipelines, applying optimization and reliability principles
Implement data quality checks, validation logic and SQL testing frameworks
Use Python for automation, API integrations and workflow enhancement
Posting record
Report an errorActively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 1, 20262 days ago
- Recorded sightings
- 4
- Last seen by us
- Nov 4, 2026
- Employer says posted
- Oct 22, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
EPAM Systems is hiring
656 open jobs
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Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- Power BI
- Tableau
Where the posting names them
We're looking for a Senior Data Engineer (Python/Tableau) to join our team in Madrid, Spain in a hybrid working mode. In this role, you will design and optimize SQL-driven data transformations, develop scalable ETL/ELT pipelines, and contribute to enterprise data models supporting analytical, financial and regulatory reporting. This position provides an opportunity to work in a dynamic financial environment, partnering with cross-functional teams to deliver clean, reliable datasets while leveraging automation, BI optimization and engineering best practices for high-impact business intelligence enablement. Responsibilities Develop and optimize complex SQL transformations to support analytics and reporting Design and extend enterprise data models (Data Vault, dimensional, 3NF) and maintain standards Implement data quality checks, validation logic and SQL testing frameworks Build and operate SQL-centric ETL/ELT pipelines, applying optimization and reliability principles Use Python for automation, API integrations and workflow enhancement Structure datasets for consumption in BI tools (Tableau, Power BI), assisting with performance and governance Partner with business stakeholders in finance, risk and compliance to translate requirements into data solutions Ensure monitoring, observability and operational stability of pipelines in production environments Follow engineering best practices including version control, documentation and CI/CD integration Contribute to platform improvement, performance tuning, and architectural roadmap initiatives Requirements Bachelor’s/Master’s degree in Computer Science, Information Systems or related field Minimum 5+ years of experience in SQL-centric data engineering or backend roles Expert-level experience in SQL development including query optimization and tuning Strong background in data modelling techniques: Data Vault, dimensional, SCD and 3NF Hands-on experience in building SQL-driven transformations and scalable data solutions Practical knowledge of Python for automation and integration tasks Familiarity with BI tools such as Tableau or Power BI for backend enablement Experience working in banking or financial environments and regulated domains is highly desirable Strong focus on data quality, reliability and maintainable solutions Excellent problem-solving, requirements refinement and stakeholder collaboration skills Hands-on experience with engineering best practices: version control, code quality and CI/CD Fluent English communication (written and spoken) Nice to have Familiarity with Temenos T24/Transact, Temenos Triple’A or similar core banking systems Exposure to observability tools, data governance frameworks and automation for data ops Experience in performance optimization and support for complex BI environments
Your next step
Complete your application on careers.epam.com. The employer’s form will show what is required.
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About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
We're looking for a Senior Data Engineer (Python/Tableau) to join our team in Madrid, Spain in a hybrid working mode. In this role, you will design and optimize SQL-driven data transformations, develop scalable ETL/ELT pipelines, and contribute to enterprise data models supporting analytical, financial and regulatory reporting. This position provides an opportunity to work in a dynamic financial environment, partnering with cross-functional teams to deliver clean, reliable datasets while leveraging automation, BI optimization and engineering best practices for high-impact business intelligence enablement. Responsibilities Develop and optimize complex SQL transformations to support analytics and reporting Design and extend enterprise data models (Data Vault, dimensional, 3NF) and maintain standards Implement data quality checks, validation logic and SQL testing frameworks Build and operate SQL-centric ETL/ELT pipelines, applying optimization and reliability principles Use Python for automation, API integrations and workflow enhancement Structure datasets for consumption in BI tools (Tableau, Power BI), assisting with performance and governance Partner with business stakeholders in finance, risk and compliance to translate requirements into data solutions Ensure monitoring, observability and operational stability of pipelines in production environments Follow engineering best practices including version control, documentation and CI/CD integration Contribute to platform improvement, performance tuning, and architectural roadmap initiatives Requirements Bachelor’s/Master’s degree in Computer Science, Information Systems or related field Minimum 5+ years of experience in SQL-centric data engineering or backend roles Expert-level experience in SQL development including query optimization and tuning Strong background in data modelling techniques: Data Vault, dimensional, SCD and 3NF Hands-on experience in building SQL-driven transformations and scalable data solutions Practical knowledge of Python for automation and integration tasks Familiarity with BI tools such as Tableau or Power BI for backend enablement Experience working in banking or financial environments and regulated domains is highly desirable Strong focus on data quality, reliability and maintainable solutions Excellent problem-solving, requirements refinement and stakeholder collaboration skills Hands-on experience with engineering best practices: version control, code quality and CI/CD Fluent English communication (written and spoken) Nice to have Familiarity with Temenos T24/Transact, Temenos Triple’A or similar core banking systems Exposure to observability tools, data governance frameworks and automation for data ops Experience in performance optimization and support for complex BI environments
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