Participate in development of database solutions for optical switch manufacturing, maintain and expand production database systems, integrate with software controlling test and automation stations.
Responsibilities
Maintain and expand functionality of production database system
Integrate database with new and existing software controlling test and automation stations
Develop stored procedures for data exchange
Create and revise software documentation
Analyze production requirements and propose data-oriented solutions
Lead Data Engineer responsible for building and evolving large scale backend data systems, real time and batch pipelines, and AI enabled services across Mastercard’s global organization.
Responsibilities
Design, develop, and maintain backend services and data pipelines using Scala, Python and Java
Build and optimize batch and streaming workloads on Cloudera Data Platform (CDP) using Spark
Work with Cloudera Manager to support platform configuration, monitoring, performance tuning, and operational stability
Design and implement high quality datamarts and curated datasets with strong emphasis on data integrity, performance, and reliability
Design, build, and integrate AI powered agents that operate to support anomaly detection and operational intelligence workflow automation
Requirements
BS/BA degree in Computer Science, Engineering, Information Systems, or related field
Act as a technical liaison between customers, service engineering teams and support, architect hybrid AWS and on-premises solutions, guide customers on architecture choices, and ensure successful deployment on AWS.
Compensation
40 hours/week, 8:00am – 5:00pm, Salary Range $141,835 - $177,600 / year
Responsibilities
Act as a technical liaison between customers, service engineering teams and support
Analyze application portfolios, identify dependencies and common infrastructure platform components, and assess migration feasibility
Architect hybrid AWS and on-premises solutions
Guide customers on architecture choices and inform them of best practices to adopt AWS efficiently and cost-effectively
Ensure success in building, migrating, and deploying applications, software and services on the AWS platform
Requirements
Master's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field with five years of experience
Senior level software integration engineer serving as the primary customer-facing operations point of contact, managing request triage, gathering and scoping technical requirements, and providing standby support for ad-hoc critical thinking requests as directed by the mission customer.
Compensation
Annual Salary: $130,000 - $270,000 (Depends on the Years of Experience)
Responsibilities
Serve as the primary customer-facing operations point of contact
Manage request triage
Gathering and scoping technical requirements
Providing standby support for ad-hoc critical thinking requests
Integrating, installing, configuring, upgrading, compiling, and supporting COTS/GOTS software in a heterogeneous operating system environment
Requirements
Bachelor's Degree in Computer Science or related field
Master's Degree in Computer Science or related field
Design and evolve data engineering solutions to calculate and analyze daily transactional profitability, impacting information quality and strategic decision-making for the Commerce business.
Responsibilities
Design and de-evolve data ingestion and data modeling pipelines that feed the daily transactional profitability model, ensuring scalability, flexibility, and robustness.
Develop and de-optimize data architectures capable of processing large volumes of information in high-traffic and high-availability environments, improving distributed processing, execution times, and infrastructure costs.
Translate functional business rules into technical solutions, working with involved teams and incorporating AI tools to generate, review, and optimize SQL code, automate tasks, and accelerate analysis.
Guarantee data quality, traceability, and timely availability, performing impact estimation and analysis of changes, promoting best practices in modeling, observability, and stability in production processes.
Requirements
Nice to have: GenAI
Nice to have: Artificial Intelligence for data engineering
Design and develop scalable ETL/ELT data pipelines using Spark, Scala, Hive, and SQL on GCP, build data warehouse solutions, optimize Big Data workloads, implement CI/CD pipelines, and support analytics and reporting through Power BI.
Locations (2)
Bengaluru, Karnataka, India
Pune, Maharashtra, India
Responsibilities
Design and develop scalable ETL/ELT data pipelines using Spark, Scala, Hive, and SQL on GCP
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