Senior Data Engineer SQL

Swisslinx AG · Zürich, Zürich, Switzerland

On-siteWorkplace
1d agoPosted · Aug 5
jobroomSource
Apply now Opens the original posting at Swisslinx AG. PivotHop does not host applications.

Skills in this posting

Extracted from the posting text by the instrument — the demand side, read literally.

The posting

Senior Data Engineer SQL

Shape trusted banking data with expert SQL, scalable pipelines, and enterprise\-grade modelling.

Senior Data Engineer SQL

Job description

SQL Development \& Data Modelling

Develop and optimize complex SQL transformations supporting analytics, reporting, and financial/regulatory needs.

Work with and contribute to existing enterprise data models (Data Vault, dimensional, 3NF, domain driven structures).

Ensure SQL logic is performant, maintainable, and aligned with modelling standards.

Implement and maintain dataquality checks, validation rules, and SQL testing.

Maintain clear documentation, lineage, and metadata to support transparency and governance.

Support reduction of architectural debt and help maintain a clean, consistent data environment.

Data Pipelines \& Integration Engineering

Build and maintain SQL centric ETL/ELT data pipelines.

Use where beneficial for automation, API integration, or workflow efficiency.

Implement ingestion patterns for batch, incremental, and near real time data flows.

Ensure monitoring, observability, and reliable operation of data workflows.

Business Intelligence Enablement

Experience with Tableau or other BI tools is a strong plus, especially for:

Structuring SQL datasets optimized for BI consumption.

Supporting data preparation, extract logic, and backend performance.

Assisting dashboard/report designers with troubleshooting, prototyping, and governance.

Cross Functional Collaboration

Partner with finance, risk, compliance, and business teams to translate requirements into high quality data solutions.

Work closely with data architects to ensure alignment with modelling standards.

Support troubleshooting across ingestion, modelling, and operational processes.

Contribute to platform evolution, engineering improvements, and roadmap initiatives.

Communicate effectively with both technical and business stakeholders.

Data Platform \& Operational Excellence

Collaborate with platform and infrastructure teams to operate SQL workloads reliably in production.

Apply engineering best practices: version control, documentation, testing, code quality.

About the customer

This established financial services organization operates in a highly regulated banking environment, delivering data\-driven solutions that support finance, risk, compliance, reporting, and business operations.

Its technology teams manage complex enterprise data platforms and structured data models, with a strong focus on reliability, governance, transparency, and performance. The organization is continuing to modernize its data landscape through scalable SQL development, automated pipelines, robust testing, and improved observability.

Collaboration is central, bringing together data engineers, architects, platform specialists, and business stakeholders to translate complex requirements into trusted data products. Based in Luxembourg, the working environment combines international exposure, agile delivery, and high engineering standards.

The culture values ownership, clear communication, continuous improvement, and practical problem solving across the full enterprise data lifecycle.

Requirements

Bachelor’s or Master’s degree in a relevant field.

5\+ years in data engineering or SQL heavy backend roles, in banking environment.

Proven experience working with structured enterprise data models.

Hands\-on experience with Data Vault (Data Vault 2\.0 preferred), including design, implementation, and maintenance of enterprise\-scale Data Vault solutions.

Strong experience with dbt (Data Build Tool), including development, testing, documentation, and deployment of data transformation pipelines.

Expert\-level SQL skills, including complex query development, performance tuning, and optimization.

Strong experience developing scalable SQL\-driven data transformations and ELT/ETL pipelines.

Experience working with and extending enterprise data models, including dimensional modeling, SCDs, and 3NF architectures.

Strong communication and stakeholder engagement abilities.

Analytical, detail oriented, and proactive problem solver.

Comfortable in agile, iterative delivery environments. jpidd74d2c6jm jit0832jm jiy26jm

Excerpt from the original listing. The full, current text lives at the source. Read and apply there →

The PivotHop read

Where these skills also reach

Adjacent occupations measured from the same postings — readiness is what a data engineer’s profile already covers.

More data engineer roles

Backfilled listing, refreshed with the nightly scrape; the employer has not claimed it yet. Are you the employer? Claim this listing and it can be featured to the candidates whose skills already reach it, first month free.

© 2026 PivotHopReal data, real career moves