Top Data & Analytics Jobs

Designs and maintains scalable ETL/ELT pipelines and batch or real-time data processing solutions using SQL, Python, and Spark. Ensures data quality, availability, and reliability through testing, monitoring, observability, and automated deployments. Supports platform upgrades, migrations, and production operations while collaborating with data and business teams. Contributes to technical reviews, documentation, architecture discussions, and engineering best practices.

Lead small data quality projects across matrixed teams, coordinate compliance communications and remediation, facilitate policy and standards education, track program KPIs, produce reports, identify risks and dependencies, and collaborate with Product, Technology, and Data Strategy teams. Support customers with data quality requirements, operational processes, issue resolution, and compliance. Use analytical and technical skills to investigate root causes, validate assumptions, and drive continuous improvement.

Design, build, and scale cloud-native data and BI solutions on Databricks and Snowflake. Develop high-performance data pipelines, enable multi-cloud interoperability (AWS/Azure), implement governance and secure access patterns, maintain CI/CD and infrastructure-as-code for platform provisioning, and lead technical design while mentoring engineers.

Develop and maintain data extraction, transformation, automation, integration, and analytics solutions for Mastercard initiatives. Build complex SQL queries, Alteryx workflows, Tableau dashboards, and Power Platform applications. Gather requirements, deliver projects end to end, optimize reporting services, communicate quantitative insights, and collaborate with technical and business stakeholders to improve operational efficiency.

Designs and supports large-scale cloud-native data platforms on AWS and Databricks. Builds batch, streaming, and real-time pipelines; engineers distributed processing with Spark; develops Lakehouse architectures using Delta Lake and Iceberg; modernizes Hadoop workloads; and implements automation, governance, security, observability, performance optimization, and cost management. Partners with architects, product managers, data scientists, and engineers to enable analytics, machine learning, and AI at petabyte scale.

Support a large card migration program by delivering data-driven insights, managing analytics workstreams, building predictive models, synthesising large datasets into recommendations, preparing client deliverables and presentations, and coordinating with cross-functional teams to ensure timely, compliant migration outcomes.

Lead analytics workstreams for clients by designing and implementing data-driven solutions, analyzing large datasets, synthesizing findings into recommendations, developing client presentations, managing stakeholders, mentoring junior consultants, and contributing to solution development and project management.

Lead GBSC data engineering and analytics initiatives: design data/ETL infrastructure, implement automation, enable large-scale structured and unstructured data analysis, manage team delivery, and communicate insights to influence business decisions.

Design, build, and optimize enterprise-scale cloud-native data platforms across AWS and Azure. Lead hands-on implementation of lakehouse architectures, ETL/ELT pipelines, IaC and CI/CD, security and governance frameworks, observability, cost optimization, and cross-team technical direction to enable scalable, secure data access for analytics and reporting.

Design, build, and operate enterprise-scale cloud-native data platforms across AWS and Azure. Lead hands-on implementation of Medallion lakehouse architectures, ETL/ELT pipelines, IaC/CI-CD, security, governance, observability, and cost optimization while influencing cross-functional teams and promoting engineering best practices.