Lead Data Engineer

Role details

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 Lead Data Engineer Overview: We are seeking an experienced Lead Data Engineer to lead the design, delivery, modernization, and operational management of enterprise data platforms, databases, data warehouses, and data engineering solutions. The role is responsible for providing technical leadership across Data Engineering, Database Administration, Cloud Data Platforms, and Data Warehouse operations while ensuring the reliability, scalability, security, and cost efficiency of the organization's data ecosystem. The ideal candidate will possess strong expertise in data engineering, database technologies, cloud platforms, data warehousing, ETL/ELT, CDC, and platform operations, combined with proven leadership experience in managing projects, driving strategic initiatives, mentoring teams, and collaborating across multiple technology functions. This role will partner closely with Data Engineering, DBA, Cloud Engineering, SRE, Security, Analytics, and Business teams to deliver scalable and business-aligned data solutions. Key Responsibilities Technical Leadership & Architecture Provide technical leadership for Data Engineering, Data Warehouse, and Database initiatives. Define and drive architecture standards, engineering best practices, and platform governance. Design scalable, secure, and high-performance data solutions across cloud and on-premise environments. Lead technical design reviews, solution assessments, and modernization initiatives. Mentor engineers and foster a culture of engineering excellence and continuous improvement. Data Engineering & Data Warehouse Design, develop, and oversee enterprise ETL/ELT and CDC pipelines. Manage data integration across relational, NoSQL, SaaS, and cloud-based platforms. Design and optimize data warehouse, lakehouse, and analytical solutions using technologies such as Snowflake, Databricks, Apache Iceberg, and Amazon S3. Ensure data quality, reliability, observability, and operational readiness of all data products. Drive adoption of reusable frameworks, automation, and standardized engineering practices. Database & Platform Management Provide oversight of enterprise database environments including PostgreSQL, MySQL, Aurora PostgreSQL, Aurora MySQL, MongoDB Atlas, and DynamoDB. Ensure database availability, performance, security, backup, recovery, and capacity planning. Collaborate with DBA, SRE, and Cloud teams on performance tuning, incident resolution, disaster recovery, and operational improvements. Establish monitoring, alerting, and operational processes for critical platforms. Project Delivery & Operations Ensure successful and timely delivery of projects through effective planning, prioritization, and execution. Track project progress, dependencies, risks, and milestones. Proactively identify and remove blockers impacting team productivity and project delivery. Lead incident management and root cause analysis activities while driving preventive actions. Continuously improve operational processes, runbooks, and service reliability. Strategic Initiatives & Optimization Drive modernization initiatives including migration from legacy platforms to cloud-native solutions. Evaluate emerging technologies and conduct proof-of-concepts to support business objectives. Lead cost optimization efforts across cloud platforms, licenses, and data infrastructure. Partner with FinOps and platform teams to improve platform utilization and operational efficiency. Identify opportunities to simplify architecture, reduce technical debt, and improve scalability. Resource & Capacity Planning Support workforce planning by forecasting resource needs for BAU activities and project initiatives. Align team objectives with business priorities, strategic initiatives, and individual development plans. Participate in hiring, onboarding, and succession planning activities. Balance workloads and capacity across multiple projects and operational responsibilities. Stakeholder & People Leadership Foster strong collaboration across Data Engineering, DBA, SRE, Cloud, Security, BI, and application teams. Establish regular stakeholder engagement to provide project updates, address challenges, and align priorities. Conduct performance reviews, career development discussions, coaching, and mentoring activities. Promote a culture of accountability, inclusion, innovation, and continuous learning. Recognize and encourage outstanding team contributions and achievements. Required Skills & Experience Core Requirements: 8+ years of experience in Data Engineering, Database Engineering, Data Warehousing, or related disciplines. Strong experience with Python, SQL, PySpark, ETL/ELT, and CDC-based architectures. Expertise in relational databases including PostgreSQL, MySQL, Aurora PostgreSQL, and Aurora MySQL. Strong understanding of database administration concepts including performance tuning, indexing, partitioning, backup/recovery, replication, and capacity planning. Experience designing and managing enterprise data warehouses, data lakes, and lakehouse platforms. Experience with cloud-based data services and modern analytics platforms. Cloud & Data Platforms: Strong expertise in AWS services including AWS Glue, S3, DMS, DynamoDB, IAM, VPC, and CloudWatch. Hands-on experience with Snowflake, Databricks, Apache Iceberg, or equivalent modern data platforms. Understanding of cloud security, governance, and cost optimization practices. Leadership & Operations: Prov