Data Engineer
Hybrid Lisbon Full-time Mid-level Data Engineering
At a glance
Mid-level Data Engineering role at Arrow Global Group. Lisbon · full-time.
Pay not stated Data Engineer salary
RoleData Engineering
SeniorityMid-level
LocationLisbon
WorkplaceHybrid
EmploymentFull-time
PostedMar 11, 2026 · 7mo ago
Role brief
dataroles summary, based on the employer's posting.
What you'll do
- Build reusable pipelines that turn raw information into relational data models, with reliability and auditability at scale
- Collect incoming data and move it into shared business data assets, including warehouse and lake environments
- Set standards for data flows and produce trusted datasets for portfolio analytics, finance, risk and asset strategy
- Tune ingestion and integration workflows, and shape pipeline designs with data stewards and business analysts
- Apply ADF, Databricks, Python, PySpark and Spark SQL expertise across complex, multi-source data
What you bring
- You have proven data engineering experience creating dependable, reusable pipelines
- You bring substantial experience with Azure data engineering tools, including ADF, Databricks, Python and Spark technologies
- You have worked with financial data such as transactions, market information or reference data
- A degree in computer science, information systems, data science or a related area is preferred
Who this fits
This mid-level role suits a collaborative, self-directed engineer who can work across business and technology teams and communicate clearly. The work centers on complex datasets from lending, property, collections and external providers, with a financial services focus. The position is hybrid in Lisbon.
From the employer
We are seeking highly skilled and experienced Azure Data Engineers to join a newly formed group concentrating on Data. Within this role you will be a key member of the team, working on a complex and challenging project within the Financial Services/Capital Markets industry. The primary focus of the role would be on building resilient, reusable Data Pipelines to extract, load, and transform raw data into a relational data model. The successful candidate will work across complex, multi-source datasets including loan servicing systems, property and valuation platforms, collections systems, and third-party data providers, delivering reliable and auditable data at scale.
- Serve as the team’s ADF, Databricks, Python, PySpark & Spark SQL technical expert
- Responsible for day-to-day collection & ingestion of raw data into corporate data assets
- Work with the team to formalize data flows and data standards
- Enable trusted datasets for portfolio analytics, asset strategy, finance, and risk
- Supervise all data ingestion & integration processes from source to target including the data warehouse, data lake, etc
- Performance tune and optimize all data ingestion and data integration processes
- Partner with Data Stewards and Business Analysts to understand the nature of the data being handled and what an optimal Data Pipeline for it should look like
- Design solutions that are aligned to the target state Data Architecture
- Degree in Computer Science, Information Systems, Data Science, or a related field is preferable
- Proven experience building resilient, reusable Data Pipelines as a Data Engineer or equivalent
- Resourceful, motivated self-starter with the ability to collaborate across business and technology
- Strong analytical, verbal, and written communication skills
- A background in financial data domains (IBOR/ABOR, transactions, market data, reference data)
- Strong experience as a Data Engineer within Real Estate, Credit, Banking, or NPL Asset Management
- Microsoft certification a plus
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