Senior Data Engineer

Jobtailor; Dublin; On-site; EUR 90,000 - 130,000; Full time

Job summary

Jobtailor is seeking an experienced Data Engineer to drive data architecture and MI insights in Dublin, Ireland. You will build and automate ETL/ELT pipelines using AWS services, ingest data from external APIs into a data lake, and create interactive QuickSight dashboards backed by complex SQL models.

You will collaborate with product, engineering, credit, and finance teams to identify improvements and shape data governance policies while owning the reporting infrastructure backlog with the

Qualifications

• Degree in a business, technical, or quantitative discipline.
• 6+ years in a data analytics or data engineering role.
• Advanced SQL skills, including building data models that power BI/reporting tools.
• Strong hands-on experience with core AWS data services: Glue, Lambda, Step Functions, EventBridge, S3, Athena.
• Proven experience building and monitoring production ETL/ELT pipelines, including reconciliation and validation.
• Proficient in Python and Spark, with hands-on experience processing and optimizing large scale data volumes.
• Experience with Amazon QuickSight (or a comparable BI tool) for dashboard and report development.
• Experience integrating third-party APIs into a data lake and data lake design principles.
• Experience working in Agile/product-led environments, managing a backlog with a Product Owner.
• Strong communication skills, with a track record of working directly with non-technical stakeholders.
• Experience in querying unstructured data (e.g., nested and repeated fields, JSON)

Responsibilities

• Play a key role in ensuring data and operational excellence across the business.
• Improve management insights (MI) and contribute to the data architecture development.
• Build, automate and monitor ETL/ELT pipelines using AWS services.
• Build ingestion pipelines pulling data from external APIs into the data lake.
• Reverse-engineer reports from legacy systems and design modern data structures.
• Develop interactive Amazon QuickSight dashboards backed by SQL models.
• Automate customer and funder statement generation via Amazon Athena.
• Build and maintain MI dashboards.
• Collaborate with product, engineering, credit, and finance to improve processes and governance.
• Own and prioritise the reporting-infrastructure backlog with the Product Owner.

Skills

Advanced SQL

Python

Spark

Data Modeling

Data Discovery

Data Processing

API Integration

Data Validation

Strong Communication Skills

Collaboration with Non-Technical Stake

Agile Environment

Education

Degree in a business, technical, or quantitative discipline

Tools

AWS Glue

AWS Lambda

AWS Step Functions

AWS EventBridge

AWS S3

AWS Athena

Amazon QuickSight

Job description

• Play a key role in ensuring that data and operational excellence prevails across all aspects of the business


• Work on improving management insights (MI) and contributing to the development of the company’s data architecture


• Build, automate and monitor ETL/ELT pipelines using AWS services (EventBridge, Step Functions, Glue, Lambda, S3)


• Build ingestion pipelines that pull data from external APIs into the data lake, enriching and linking it with banking data


• Perform data discovery and reverse-engineer reports from legacy systems then design the data structures needed to replace them in the modern platform


• Develop interactive Amazon QuickSight dashboards backed by complex SQL models


• Automate customer and funder statement generation via Amazon Athena


• Build and maintain Management Information (MI) dashboards


• Partner with product, engineering, credit, and finance teams to identify process improvements, recommend system changes, and shape data governance policy


• Own and prioritise the reporting-infrastructure backlog alongside the Product Owner

Requirements

• Degree in a business, technical, or quantitative discipline


• 6+ years in a data analytics or data engineering role


• Advanced SQL skills, including building data models that power BI/reporting tools


• Strong hands‑on experience with core AWS data services: Glue, Lambda, Step Functions, EventBridge, S3, Athena


• Proven experience building and monitoring production ETL/ELT pipelines, including reconciliation and validation


• Proficient in Python and Spark, with hands‑on experience processing and optimizing large scale data volumes


• Experience with Amazon QuickSight (or a comparable BI tool) for dashboard and report development


• Experience integrating third‑party APIs into a data lake and a solid grasp of data lake design principles


• Experience working in Agile/product‑led environments, managing a backlog with a Product Owner


• Strong communication skills, with a track record of working directly with non‑technical stakeholders


• Experience in querying unstructured data (e.g., nested and repeated fields, JSON)

Core Competencies

Demonstrates expertise in building and automating ETL/ELT pipelines using AWS services, advanced SQL for data modeling, and developing interactive dashboards with Amazon QuickSight. Strong collaboration with cross‑functional teams to enhance data governance and operational excellence is essential.

Highest-signal resume keywords

• ETL/ELT Pipeline Development


• Advanced SQL Skills


• AWS Data Services (Glue, Lambda, Step Functions, EventBridge, S3, Athena)


• Data Lake Design Principles


• Amazon QuickSight Dashboard Development

ATS Optimization Keywords

Hard Skills

• ETL/ELT Pipeline Development


• Advanced SQL


• Python


• Spark


• Data Modeling


• Data Discovery


• Data Structure Design


• API Integration


• Data Processing


• Data Validation

Soft Skills

• Strong Communication Skills


• Collaboration with Non‑Technical Stakeholders

Industry Keywords

• Data Analytics


• Data Engineering


• Agile Environment


• Management Information (MI)


• Data Governance

Tools & Technologies

• Amazon QuickSight


• AWS Glue


• AWS Lambda


• AWS Step Functions


• AWS EventBridge


• AWS S3


• AWS Athena