As a Lead Software Engineer, you will design and build scalable data pipelines, lead technical execution, and improve platform quality. You will collaborate with data scientists and product managers, address technical debt, and mentor other engineers.
Our Purpose
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
Title and Summary
Lead Data Engineer - Data Pipelines
Economic Intelligence is a Mastercard Services program within Economic & Business Intelligence (EBI). The program delivers macro-to-micro economic and market insights powered by Mastercard data, analytics, and research. Our goal is to help customers understand economic trends, benchmark performance, forecast outcomes, and make informed strategic decisions across geographies and industries.[BB1]
As an engineering team, we analyze billions of transactions globally and build platforms that deliver insights into historical consumer spending, forecasts of future spending, and expert commentary on the current economic climate. Our customers span financial services, retail, and government sectors worldwide. We are actively expanding our platform capabilities and work closely with Data Scientists and Product Managers to deliver reliable, flexible, and scalable solutions.
The Engineering organization consists of two main squads: Data Pipeline (Python, SQL, Databricks) and UI & Publishing (.NET, React). Team members may be dedicated to a squad or contribute across multiple workstreams depending on program priorities. Economic Intelligence owns a portfolio of products and ad-hoc deliverables at varying levels of maturity, resulting in a diverse scope of work from clarifying requirements and designing new capabilities to addressing technical debt and evolving a unified data layer.
Position Responsibilities
As a Lead Data Engineer with a primary focus on the Data Pipeline team, you will:
Lead technical execution to deliver end-to-end capabilities from data processing through publishing and customer consumption.
Design, build, and evolve scalable, maintainable data pipelines that deliver insights from economic data.
Drive performance, reliability, observability, and readability in the data platform codebase, enabling rapid troubleshooting and consistent publishing of data outputs.
Own and unify the data layer across multiple products, establishing shared patterns, reusable components, and clear interfaces that support both pipeline and publishing workflows.
Translate business needs into durable technical designs. Clarify ambiguous problem spaces and requirements by partnering with Data Science, Product Management, and external stakeholders.
Tackle technical debt strategically, prioritizing work that improves platform quality, reduces operational burden, and accelerates delivery across the portfolio. Communicate risks and requirements to senior stakeholders.
Set engineering direction and standards for pipeline development and cross-team integration, including code quality, testing strategy, design documentation, and review practices.
Write, test, and review code. Provide technical leadership through mentorship, rigorous code reviews, and support for other engineers' growth and delivery.
Continuously innovate, evaluating new approaches, tools, and technologies (including AI adoption, Cloud and Workflow orchestration) to solve business problems and improve delivery.
Ideal Candidate Qualifications
We're looking for a lead data engineer who brings both strong hands-on capability and pragmatic technical leadership:
Strong professional experience with Python building production-grade systems (required).
Strong SQL skills, including writing readable and well-tuned queries for large-scale datasets (required).
Experience leading design and delivery of data pipelines and/or data platform components, with attention to scalability, reliability, and maintainability.
Familiarity with Databricks (or similar Spark-based data platforms) and enthusiasm to expand usage as the product footprint grows.
Comfortable using LLM-based coding tools, with the discipline to validate, test, and take full ownership of the generated code.
Strong foundation in object-oriented software design and engineering best practices.
Comfortable with Linux command line and production troubleshooting.
Clear communicator with strong written and verbal English; able to explain technical concepts to teammates with varying levels of technical depth (required).
Ownership mindset: motivation, creativity, self-direction, and ability to thrive in small, collaborative teams while influencing across boundaries.
Passion for analytical/quantitative problem solving, quality, and continuous improvement of both platform and team processes.
Nice to have:
Experience with C# or another strongly-typed object-oriented language, and ability to collaborate effectively with .NET/React engineers on integration points between pipelines and publishing/UI systems.
Experience with workflow orchestration (Airflow).
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
Title and Summary
Lead Data Engineer - Data Pipelines
Economic Intelligence is a Mastercard Services program within Economic & Business Intelligence (EBI). The program delivers macro-to-micro economic and market insights powered by Mastercard data, analytics, and research. Our goal is to help customers understand economic trends, benchmark performance, forecast outcomes, and make informed strategic decisions across geographies and industries.[BB1]
As an engineering team, we analyze billions of transactions globally and build platforms that deliver insights into historical consumer spending, forecasts of future spending, and expert commentary on the current economic climate. Our customers span financial services, retail, and government sectors worldwide. We are actively expanding our platform capabilities and work closely with Data Scientists and Product Managers to deliver reliable, flexible, and scalable solutions.
The Engineering organization consists of two main squads: Data Pipeline (Python, SQL, Databricks) and UI & Publishing (.NET, React). Team members may be dedicated to a squad or contribute across multiple workstreams depending on program priorities. Economic Intelligence owns a portfolio of products and ad-hoc deliverables at varying levels of maturity, resulting in a diverse scope of work from clarifying requirements and designing new capabilities to addressing technical debt and evolving a unified data layer.
Position Responsibilities
As a Lead Data Engineer with a primary focus on the Data Pipeline team, you will:
Lead technical execution to deliver end-to-end capabilities from data processing through publishing and customer consumption.
Design, build, and evolve scalable, maintainable data pipelines that deliver insights from economic data.
Drive performance, reliability, observability, and readability in the data platform codebase, enabling rapid troubleshooting and consistent publishing of data outputs.
Own and unify the data layer across multiple products, establishing shared patterns, reusable components, and clear interfaces that support both pipeline and publishing workflows.
Translate business needs into durable technical designs. Clarify ambiguous problem spaces and requirements by partnering with Data Science, Product Management, and external stakeholders.
Tackle technical debt strategically, prioritizing work that improves platform quality, reduces operational burden, and accelerates delivery across the portfolio. Communicate risks and requirements to senior stakeholders.
Set engineering direction and standards for pipeline development and cross-team integration, including code quality, testing strategy, design documentation, and review practices.
Write, test, and review code. Provide technical leadership through mentorship, rigorous code reviews, and support for other engineers' growth and delivery.
Continuously innovate, evaluating new approaches, tools, and technologies (including AI adoption, Cloud and Workflow orchestration) to solve business problems and improve delivery.
Ideal Candidate Qualifications
We're looking for a lead data engineer who brings both strong hands-on capability and pragmatic technical leadership:
Strong professional experience with Python building production-grade systems (required).
Strong SQL skills, including writing readable and well-tuned queries for large-scale datasets (required).
Experience leading design and delivery of data pipelines and/or data platform components, with attention to scalability, reliability, and maintainability.
Familiarity with Databricks (or similar Spark-based data platforms) and enthusiasm to expand usage as the product footprint grows.
Comfortable using LLM-based coding tools, with the discipline to validate, test, and take full ownership of the generated code.
Strong foundation in object-oriented software design and engineering best practices.
Comfortable with Linux command line and production troubleshooting.
Clear communicator with strong written and verbal English; able to explain technical concepts to teammates with varying levels of technical depth (required).
Ownership mindset: motivation, creativity, self-direction, and ability to thrive in small, collaborative teams while influencing across boundaries.
Passion for analytical/quantitative problem solving, quality, and continuous improvement of both platform and team processes.
Nice to have:
Experience with C# or another strongly-typed object-oriented language, and ability to collaborate effectively with .NET/React engineers on integration points between pipelines and publishing/UI systems.
Experience with workflow orchestration (Airflow).
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
- Abide by Mastercard's security policies and practices;
- Ensure the confidentiality and integrity of the information being accessed;
- Report any suspected information security violation or breach, and
- Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.
Top Skills
.Net
Databricks
Python
React
SQL
Mastercard Saint Leonards, Victoria, AUS Office
72 Christie St, Saint Leonards, St Leonards, Australia, NSW 2065
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