SAS / Data Engineer at Bridge 351
At a glance
- Company
- Bridge 351
- Location
- Portugal
- Work arrangement
- On-site
- Employment type
- Full-time
- Experience
- 5–10 years
- Working hours
- 40 hours
- Visa sponsorship
- Offered, according to the listing
- Posted
- Added to The Stack
✨ The Stack take on this Bridge 351 job
- 🏢 Bridge 351 has 14 jobs here, 14 with visa sponsorship see all
- 🛂 Visa: EU Blue Card. Salary: At least 1.5 times the national average annual salary (1.2 times in some cases) guide
- 💡 No salary shown. Ask Bridge 351 if it is above the minimum.
Updated 2026-11-03, from our data and official sources.
Apply for this role at Bridge 351
Apply with your AI assistant
With The Stack connected to Claude, ChatGPT or Cursor, paste this. Your assistant tailors your CV and cover letter, checks the visa facts and gives you the apply link.
Help me apply to this job on The Stack: https://jobs.trythestack.co/jobs/sas-data-engineer-bridge-351
Not connected yet? Connect in a minute. To help your user apply, call the MCP tool prepare_application with slug "sas-data-engineer-bridge-351": it returns the apply link, the visa facts and a CV and cover letter checklist. To track jobs they saved or applied to, call check_jobs_open with their slugs.
About the role
Responsibilities:
- Work with business teams to gather requirements, map existing processes, and capture underlying business rules.
- Analyse and interpret existing SAS code and workflows to identify data sources, transformations, dependencies, and outputs.
- Document processes, data flows, and business rules to support migration decisions.
- Define migration approach to Databricks/Fabric and assist in developing, testing, and validating migrated jobs.
- Reconcile results between SAS and the new platform; liaise with technical and business stakeholders to resolve discrepancies.
Requirements:
- Hands-on experience maintaining and analysing SAS code and processes.
- Strong SQL skills and solid understanding of data transformation, ETL/ELT, and data pipelines.
- Experience gathering requirements and documenting processes and business rules for migration projects.
- Familiarity with Databricks/Fabric concepts and practical data-processing knowledge.
- Good communication, autonomy, and collaboration skills; Python/PySpark and prior migration experience are advantageous.
Responsibilities
You will analyze and document existing SAS processes to facilitate their migration to modern platforms like Databricks and Fabric. Additionally, you will collaborate with business teams to define requirements and validate the accuracy of migrated data solutions.
Requirements
The role requires hands-on experience with SAS code maintenance and strong SQL skills for data processing. Candidates should also possess experience in requirements gathering and have a collaborative mindset for working with cross-functional teams.
Key skills
- SAS — in 2 other listings on The Stack
- Data engineering — in 118 other listings on The Stack
- Databricks — in 41 other listings on The Stack
- Fabric — not in any other listing on The Stack
- SQL — in 527 other listings on The Stack
- Data transformation — in 8 other listings on The Stack
- Business rules — not in any other listing on The Stack
- Requirements gathering — in 6 other listings on The Stack
- Process documentation
- Python
- PySpark
- ETL
- ELT
- Data migration
- Data pipelines
- Communication
On The Stack (as of 2026-11-03)
Frequently asked questions about Bridge 351
Is this SAS / Data Engineer role still open?
It was posted on 2026-11-02 and is listed as active on The Stack. Confirm on Bridge 351's application page before applying.
Does Bridge 351 offer visa sponsorship?
This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on Bridge 351's site.
Where is this role located?
The listing gives the location as Portugal. It is marked on-site.
What skills does this role ask for?
The listing names: SAS, Data engineering, Databricks, Fabric, SQL, Data transformation, Business rules, Requirements gathering, Process documentation, Python, PySpark, ETL, ELT, Data migration, Data pipelines, Communication.