Manager - Data Engineering

About the job

Job Title: Manager - Data Engineering Overview: Job Description Product Data & Analytics Team Manager – Data Engineering Overview Product Data & Analytics team builds internal analytic partnerships, strengthening focus on the health of the business, portfolio and revenue optimization opportunities, initiative tracking, new product development and Go-To Market strategies. • Are you excited about Data Assets and the value they bring to an organization? • Are you an evangelist for data driven decision making? • Are you motivated to be part of a Global Analytics team that builds large scale Analytical Capabilities supporting end users across 6 continents? • Do you want to be the go-to resource for data analytics in the company? The ideal candidate has a knack for seeing solutions in sprawling data sets and the business mindset to convert insights into strategic opportunities for our company. Role & Responsibilities: • Work closely with global & regional teams to architect, develop, and maintain data pipelines on large volumes of data in order to support analytics and reporting needs across products, markets and services. • Lead cross-functional projects using advanced data engineering and analysis techniques to enable data for insights that will guide strategic decisions and uncover optimization opportunities. • Build, develop and maintain data models, ETL / data pipelines, data automation systems, datalakes, data warehouse that support key business decisions. • Translate business requirements into tangible technical solution specifications and high quality, on time deliverables. • Create reusable processes to support development of data ingestion, data transformation, data quality and testing frameworks. • Effectively use tools to manipulate large-scale databases, synthesizing data insights. • Apply quality control, data validation, and cleansing processes to new and existing data sources. • Recruit, train, develop and supervise data engineer & analyst-level employees. All About You: • Experience in data engineering, data management, data product development and quantitative analysis • Financial Institution or a Payments experience a plus • Advanced SQL skills, ability to write optimized queries for large data sets (Big data) • Experience in building data pipelines, data lakehouses, data warehouses. • Experience on Platforms/Environments: Databricks, Cloudera Hadoop, Big data technology stack and SQL Server • Experience with cloud platforms such as AWS or Azure. • Experience with Pyspark, Python and Hive. • Experience on SQL Server Integration Services (SSIS), SQL Server Analysis Services (SSAS) and SQL Server Reporting Services (SSRS) will be an added advantage • Excellent problem solving, quantitative and analytical skills • In depth technical knowledge, drive and ability to learn new technologies • Experience presenting data findings in a readable and insight driven format. Experience building support decks. • Strong attention to detail and quality • Team player, excellent communication skills • Must be able to interact with management, internal stakeholders and collect requirements • Must be able to perform in a team, use judgment and operate under ambiguity Education: • Bachelor’s or Master’s Degree in a Computer Science, Information Technology, Engineering, Mathematics, Statistics, M.S./M.B.A. preferred Additional Competencies: • Excellent English, quantitative, technical, and communication (oral/written) skills • Analytical/Problem Solving • Strong attention to detail and quality • Creativity/Innovation • Self-motivated, operates with a sense of urgency • Project Management/Risk Mitigation • Able to prioritize and perform multiple tasks simultaneously To find US Salary Ranges, visit People Place. Under the Compensation tab, select "Salary Structures." Within the text of "Salary Structures," click on the link "salary structures 2025," through which you will be able to access the salary ranges for each Mastercard job family. For more information regarding US benefits, visit People Place and review the Benefits tab and the Time Off & Leave tab.

Requirements

• Data Engineering
• Data Management
• SQL
• Data Visualization
• Data Analysis

Qualifications

• Bachelor’s or Master’s Degree

Preferred Technologies

• Data Engineering
• Data Management
• SQL
• Data Visualization
• Data Analysis