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Sr Data Engineer

Mifinity
Dublin, County Dublin

Quick apply

Job details

Full-time

Benefits

Free parking
Additional leave
Company pension

Qualifications

Data modelling
Law
Master's degree
SQL
AWS
Analysis skills
Docker
PostgreSQL
Terraform
Scripting
GitHub
Predictive analytics
S3
Apache
Redshift
Communication skills
Python

Full job description

About MiFinity

MiFinity is a globally regulated fintech company providing innovative payment processing solutions to merchants and consumers worldwide. We operate in a fast-paced, compliance-driven environment where data is at the heart of everything.

We are looking for a Senior Data Engineer to join our Data Team and play a central role in building, scaling, and maintaining the data infrastructure that drives our platform and business decisions.

Role Overview

As a Senior Data Engineer, you will work across the full stack of our modern data stack designing and building robust data pipelines, optimising data warehouse architecture, and contributing to AI/ML initiatives. You will collaborate closely with cross-functional stakeholders including Development, Compliance, Finance, Product, and Engineering to deliver high-quality, reliable data solutions in a regulated fintech environment.

Benefits:

Private Healthcare and Dental care post probation
Continuous Development Program sponsoring further education through courses and workshops.
Free parking (first come first serve basis)
Remote work allowance post probation beginning at 3 weeks in year 1 and increasing with tenure
Additional special leave days such as extra day for birthday/moving home, extra days for marriage, graduation, citizenship ceremony
Study and Exam Leave to further support career and educational growth.
Generous company pension scheme with employer matching.

Key Responsibilities

Design, build, and maintain scalable data pipelines and ETL/ELT workflows using Apache Airflow and related orchestration tooling.
Architect and optimise data warehouse data models in Amazon Redshift and PostgreSQL, including incremental loading strategies and real time data sreaming and whilst making sure that the system performs at the highest level.
Develop and maintain DBT models for analytics and reporting layers, ensuring data quality and lineage.
Build and operate real-time and near-real-time data streaming solutions using Apache Flink.
Contribute to AI/ML proof-of-concepts and production workloads, including delivery of Agentic AI via MCP for anomaly detection, predictive analytics, and NLP-based tooling.
Support AML/compliance data requirements, including regulatory reporting (e.g., FIAU/MFSA) and transaction monitoring pipelines.
Manage and improve AWS-based data infrastructure (Redshift, DBT, RDS PostgreSQL, S3, DMS, MWAA, Bedrock, Sagemaker, Apache Flink).
Collaborate with the team to define data contracts, improve observability utilising tools such as Datadog, OpenLineage and maintain data documentation.
Evaluate and architect new data tooling and integrations as the platform evolves.

Requirements

Technical Skills

Expert-level proficiency in SQL with the ability to write and optimise complex analytical queries across large datasets which require as well in depth database expertise.
Expert-level proficiency in Python for data engineering, scripting, automation, and pipeline development.
Strong hands-on experience with PostgreSQL including performance tuning, indexing strategies, partitioning, and DBA-level understanding of internals.
Minimum 3 years of experience with Apache Airflow — DAG design, TaskFlow API, scheduling, sensor patterns, and production operations.
Minimum 3 years of hands-on experience with AWS data services (Redshift, DBT, RDS PostgreSQL, S3, DMS, MWAA, Bedrock, Sagemaker).
Hands-on experience with Apache Flink for real-time data streaming, CDC pipelines, or event-driven architectures.
Proven experience architecting and selecting data tooling which includes evaluating and implementing orchestration frameworks, data quality tools, ingestion platforms, or observability solutions.
Exposure to Machine Learning concepts and workflows with a minimum 3 years working with or supporting ML pipelines, model training/serving, or applied ML in a production setting.
Demonstrable exposure to AI Agentic technologies and an active interest in applying AI/LLM capabilities within data engineering workflows.
Exposure to Monitoring platforms such as Datadog, OpenLineage and Cloudwatch or related tooling
Demonstared experience building data warehouse technologies such as Amazon Redshift with strong internal understanding incudling but not limited to, distribution styles, sort keys, and query optimisation.

Nice to Have

Experience with DBT (data build tool) for transformation layer management.
Familiarity with data observability platforms such as Datadog, OpenLineage and Cloudwatch or.
Experience in regulated industries (fintech, payments, AML/compliance).
Familiarity with Amazon Redshift internals, distribution styles, sort keys, and query optimisation.
Experience with infrastructure-as-code (Terraform, CloudFormation) or containerised deployments (Docker, Fargate), with github pipeline orchestration experience.

What We Value in a Team Member

Strong analytical mindset with the ability to break down complex problems and deliver pragmatic solutions.
Excellent communication skills able to convey technical concepts clearly to both technical and non-technical stakeholders.
A collaborative and proactive approach to working within a small, high-impact team.
Ownership mentality and comfortable taking responsibility for deliverables end-to-end.
Adaptability and willingness to work across a broad scope, from infrastructure to analytics to compliance, marketing, business development and other key areas as deemed necessary.

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