Lead Data Engineer

Mastercard; Ireland; On-site; EUR 120,000 - 180,000; Full time

Job summary

Mastercard is seeking a Lead Data Engineer to build and scale data platforms powering credit decisioning, risk analytics, and regulatory reporting.

You will lead enterprise data platform design, implement scalable ETL/ELT pipelines, and ensure data quality and governance across cloud environments. Collaboration with product, risk, analytics, and architecture teams is essential to drive innovation and operational excellence.

Qualifications

• Bachelor’s degree or 10+ years in related field.
• Hands-on data engineering leadership required.
• Experience with cloud data platforms (Azure, AWS or GCP).
• Expertise in data governance and quality.
• Strong communication with stakeholders.
• Experience with ETL/ELT architectures.

Responsibilities

• Lead the design and evolution of enterprise-grade data platforms and pipelines.
• Architect scalable ETL/ELT frameworks and data integration solutions.
• Establish data quality, lineage, governance, observability and monitoring.
• Mentor engineers and raise technical capability across the organization.
• Partner with Risk, Product, Architecture and Engineering to translate requirements into scalable solutions.
• Define engineering standards, testing, deployment automation and operational excellence.

Skills

Data engineering

Leadership

CI/CD

Python

SQL

Databricks

Apache Spark

Delta Lake

Data modeling

Security/compliance

Cloud platforms

Airflow

Java

Education

Bachelor’s degree or 10+ years experience in related field

Tools

Databricks

Apache Spark

Airflow

Delta Lake

Hadoop

Job description

• The Enterprise Credit Risk (ECR) team is seeking a Lead Data Engineer to help build and scale the next generation of data platforms that power credit decisioning, portfolio risk management, regulatory reporting, analytics, and AI-driven insights across Mastercard’s lending and risk ecosystems
• This individual will lead the design and implementation of modern data engineering solutions spanning cloud platforms, large-scale data processing, data governance, and operational excellence
• This role will partner closely with Product Management, Risk Analytics, Data Science, Architecture, and Business stakeholders to simplify access to trusted data and accelerate innovation across the ECR program
• Lead the design, development, and evolution of enterprise-grade data platforms and pipelines supporting credit risk products, decisioning capabilities, and analytics solutions
• Architect and implement scalable ETL/ELT frameworks utilizing Databricks, Spark, Delta Lake, and cloud-native technologies
• Establish data quality, lineage, governance, observability, and monitoring capabilities to ensure trusted and compliant data products
• Drive the migration and modernization of legacy data assets into cloud-based architectures and Data Lakehouse platforms
• Partner with Risk, Product, Architecture, and Engineering teams to translate business requirements into scalable technical solutions
• Define and promote engineering standards, coding practices, testing frameworks,Data Quality frameworks, deployment automation, and operational excellence across the data ecosystem
• Lead technical design reviews and influence architectural direction for data-intensive applications and services
• Optimize large-scale data processing workloads for performance, reliability, scalability, and cost efficiency
• Enable AI and advanced analytics initiatives through creation of high-quality, reusable, governed data products
• Mentor, coach, and raise the technical capability of engineers across the organization by fostering a culture of ownership, continuous learning, accountability, and engineering excellence
• Shape strategic roadmap planning, technology evaluation, and delivery priorities across the ECR portfolio, balancing business outcomes, engineering feasibility, risk, compliance, and long-term platform sustainability
• Support regulatory, compliance, security, and audit requirements through robust engineering controls and documentation
• Own complex problems with dependencies across multiple services and facilitate cross-functional collaboration to drive resolution
• Conduct technical interviews, assess engineering talent, and contribute to raising the overall performance bar of the organization

Ideal Candidate

• The ideal candidate combines deep hands-on engineering expertise with technical leadership, enabling teams to build reliable, scalable, governed, and high-quality data products
• Working knowledge of CI/CD pipelines, infrastructure-as-code, automated testing, and DevOps practices
• Experience with Data formats ( Parquet, Avro, ORC )
• Experience building and operating cloud-based data platforms on Azure, AWS, or GCP
• Experience implementing data quality frameworks, lineage, metadata management, and governance practices
• Expertise developing enterprise-grade ETL/ELT pipelines, streaming architectures, and data integration frameworks
• Demonstrated leadership in aligning engineering teams around shared goals, driving delivery through ambiguity, and creating clarity for stakeholders across product, risk, analytics, architecture, and operations
• Strong understanding of data modeling techniques for analytical and operational workloads
• Strong expertise in designing and implementing large-scale data engineering solutions and distributed data processing systems
• Advanced proficiency with Databricks, Apache Spark, Delta Lake, SQL, and Python
• Excellent communication skills with the ability to collaborate effectively across technical and business functions
• Strong understanding of security, privacy, and compliance requirements associated with sensitive financial and customer data
• Proven ability to lead technical initiatives across multiple teams and influence engineering direction without direct authority
• Ability to influence senior technical and business stakeholders, make thoughtful trade-off decisions, and guide teams toward pragmatic solutions that improve credit risk outcomes and operational resilience
• Knowledge of Java Based application development is a huge Plus
• Experience with Workflow orchestration Tools like Airflow
• Promote a high-accountability culture focused on quality, reliability, security, compliance, and continuous improvement
• Communicate effectively with senior stakeholders and clearly articulate trade-offs, risks, dependencies, and delivery progress
• Develop engineering talent through mentoring, knowledge sharing, design guidance, and constructive feedback
• Create clarity in complex, ambiguous environments by translating business needs into actionable technical direction and execution plans
• Lead by influence across engineering, product, risk, analytics, and architecture teams to align priorities and deliver measurable business outcomes
• Delta Lake
• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related STEM discipline or alternative minimum of 10 years of experience in a related field
• DatabricksApache Spark / PySparkHadoopPythonSQL