• Translate business requirements into specifications that will be used to implement the required reports and dashboards • Work with business units to gather requirements, development and delivery of business intelligence & reporting services and lead end to end Data delivery • Develops and implements business intelligence & analytics to support organizational initiatives • Build rich and dynamic dashboards using out-of-box features, customizations, and visualizations • Design and publish custom dashboards for business functions, stakeholders, and corporate users around the company • Design, model, develop & optimize stored procedures to meet data management and data reporting objectives • Design and model data flows and ETL procedures ensuring data quality and integrity • Troubleshoot and resolve issues with the processes used and the content produced by the BI platform • Provide ongoing maintenance support through troubleshooting, report modifications and optimization

• Design and develop an ingestion process for big data processing • Translate business requirements into specifications for the data ingestion process • Understand and deliver data solutions leading to end-to-end delivery • Develop and implement data pipelines to support organizational initiatives • Build and maintain ETL (Extract, Transform, Load) or ELT (Extract, Load, Transform) pipelines to move data from various sources • Ensure data accuracy, consistency, and compliance with policies and regulations • Collaborate with data scientists, analysts, and other stakeholders to meet data needs • Optimize data systems for efficiency, scalability, and performance • Create functional and technical design documents and maintain documentation for data processes

This is a full time, remote Summer Internship that can be based anywhere in the United States or Canada. We are looking for a Software Engineering Intern to join our Products organization for the Summer. In this role, you will be part of a unique and award-winning internship program within the company. The program provides the opportunity to learn new skills through training and on the job learning. The duration of the program is expected to be 90 days. The intern will join the software engineering and analytics team to design, develop, and optimize cloud based workflows and data processing applications. The role involves working with technologies such as Python, AWS, and Elasticsearch to create reliable and scalable solutions that support analytics and system monitoring. Success in this position means writing clean, efficient code, learning modern engineering practices, and collaborating closely with experienced team members. This internship offers exposure to real-world production systems, mentorship opportunities, and hands-on experience at the intersection of software engineering, data analytics, and emerging AI frameworks. Responsibilities and Duties: - Develop and maintain Python-based applications and automation workflows. - Build and enhance software pipelines that collect, process, and organize data from multiple sources. - Support and deploy solutions using cloud services such as AWS Lambda, InfluxDB, or equivalent GCP tools. - Analyze structured and unstructured data, including timeseries and network telemetry data, to identify key patterns. - Contribute to creating and maintaining analytics components using Elasticsearch and Kibana or equivalent. - Collaborate with engineers using Git, CI/CD workflows. - Document technical processes, write reusable code, and implement best practices for system reliability. - Explore new technologies such as agentic AI frameworks (e.g., LangGraph) and LLM-based automation solutions. ​ Qualifications: - Currently enrolled in a college degree program in Computer Science, Computer Engineering, Software Engineering, or a related field. - Proficiency in Python for backend development, scripting, or automation. - Understanding of data pipeline and integration concepts — collecting, transforming, and preparing data for analytics. - Exposure to AWS cloud services (Lambda, InfluxDB) or corresponding GCP components. - Familiarity with version control systems such as Git. - Experience with analytics or data‑driven projects through coursework, internships, or research. - Strong foundation in data structures, algorithms, and API design. - Excellent problem-solving skills, attention to detail, and ability to work collaboratively. - Preferred: Knowledge of the Elasticsearch Stack (Elasticsearch, Kibana, Beats, Logstash) or equivalent. - Preferred: Exposure to agentic or autonomous system development and machine learning workflows. - Knowledge of timeseries data or network telemetry data is a plus. - Able to work for the complete summer break (May - August or June - September). #LI-Remote The base pay range for this position varies based on the geographic location. More information about the pay range specific to candidate location and other factors will be shared during the recruitment process. Individual pay is determined based on location of residence and multiple factors, including job-related knowledge, skills and experience. San Francisco Bay Area: 27.60 - 34.50 USD HourlyAll Other US Locations: 24.00 - 30.00 USD Hourly For information on our benefits click here.

• Design, build, and maintain efficient data pipelines (ETL/ELT processes) using Apache Spark on AWS EMR to integrate data from various source systems into our data warehouse and data lake. • Build and optimize batch and near real-time data processing jobs on Spark (including performance tuning, partitioning, and cost control on EMR) to support analytics and reporting needs. • Write and refine complex SQL queries and use scripting (e.g., Python) to transform and aggregate large datasets. • Implement data quality measures (such as validation checks and cleansing routines) to ensure data integrity and reliability. • Develop and optimize data warehouse schemas and tables, and define contracts between Spark/EMR pipelines, Iceberg tables, Snowflake models, and dbt transformations. • Collaborate with data analysts, data scientists, and other engineers to understand data requirements and deliver appropriate solutions. • Document pipeline designs, data flows, and data definitions for transparency and future reference, adhering to team standards. • Handle multiple tasks or projects simultaneously, prioritizing work and communicating progress to stakeholders to meet deadlines.