A Data Analyst develops computer programs to analyze large customer information databases for companies and organizations. Analyzes data to identify patterns and provide information relevant to a particular business, industry or field; analysis may be used for marketing, or to detect fraud in financial transactions, or for research. Develops computer programs to protect confidential customer information.
Data Analysis and Development Analyze customer data, event, and large-scale datasets to generate insights, validate data quality, and support business decision-making. Write, optimize, and maintain advanced SQL queries across Presto, Hive, and NoSQL systems. Use Python to support data processing, automation, workflow operations, and API integrations. Work within cloud platforms (primarily AWS) and apply general cloud data architecture principles. Perform exploratory data analysis to validate assumptions, identify anomalies, and support stakeholder requirements. Document data processes, business rules, logic, and workflows in Confluence or similar platforms. Collaborate with engineering, analytics, marketing, CRM teams, and SMEs to define data requirements and ensure accuracy. Operate CDP workflow orchestration tools (e.g., Digdag, TD Workflows) to manage pipelines and scheduled jobs. Enhance and monitor data quality frameworks including validation checks, alerts, and pipeline observability. Follow CI/CD and Git-based version control best practices for SQL, scripts, and documentation. Ensure adherence to privacy and compliance standards (GDPR, CCPA, PII). Solve end-to-end data challenges from ingestion through transformation to analysis and activation. Maintain rigorous attention to detail, especially with customer-level and production data. Proactively improve automation, data quality, workflow reliability, and system performance. Communicate insights and technical concepts clearly to both technical and non-technical audiences. Partner with SMEs to understand business context, refine requirements, and validate solution accuracy Troubleshooting & Support Diagnose and resolve data pipeline failures, ingestion issues, and workflow errors in a timely manner. Perform root cause analysis using logs, pipeline metadata, and system monitoring tools. Support production environments by monitoring scheduled jobs, validating outputs, and ensuring data accuracy and availability. Implement fixes, patches, and process improvements to prevent recurring problems. Maintain clear documentation of issues, resolutions, and preventive actions to strengthen operational reliability.
WHAT THIS PERSON WILL BE WORKING ON
As a Data Analyst / CDP Developer, the candidate will support the customer data platform (CDP), improve data quality, implement scalable data solutions, and address end to end data challenges. This role requires advanced SQL development, CDP integration, pipeline operations, and troubleshooting across large scale datasets. The ideal candidate is highly analytical, detail oriented, and thrives in a fast paced, cross functional environment WANTS Bachelor's degree in Data Science, Computer Science, Information Systems, Engineering, or a related field. 5+ of combined experience across data analysis, data engineering, or data operations. Advanced SQL and Query Optimization (Presto, Hive, NoSQL) Expertise in writing complex SQL queries optimizing them for large-scale datasets. Experience with Customer Data Platforms (CDP) and CRM Systems Hands-on experience integrating and managing CDP solutions and CRM platforms to unify and activate customer data. Strong SQL expertise, including complex joins, window functions, CTEs, performance optimization. Proficiency with Python for data processing, automation, and APIs. Experience working with customer data, event data, and large-scale datasets. Familiarity with cloud environments such as AWS, Google Cloud Platform, or Azure (S3, IAM, data storage concepts). Ability to perform exploratory analysis, validate data quality, and present insights to stakeholders. Understanding of data modeling, schema design, identity resolution, and profile unification. Comfortable documenting processes, transformations, and analytical logic in Confluence or similar platforms. Strong communication skills and the ability to work with cross-functional teams Hands-on experience with Treasure Data CDP or similar CDPs (Treausure Data Amperity, mParticle, Tealium etc). Experience with workflow orchestration tools (Digdag Workflows). Experience with data quality frameworks, monitoring, alerting, and pipeline observability. Experience with CI/CD, Git, and version control best practices. Understanding of privacy and compliance (GDPR, CCPA, PII handling). Provide support to production environment Strong problem-solving skills and the ability to deliver end-to-end solutions from data ingestion to analysis. Excellent attention to detail, especially when working with customer-level and production data. Proactive mindset for improving data quality, automation, and system reliability. Ability to collaborate closely with Subject Matter Experts (SMEs) to understand domain context, validate requirements, and ensure the accuracy and alignment of data solutions. John Prashanth Senior Analyst-Talent Acquisition i Space, Inc. Information Technology Services Company 840 Apollo Street, Suite 100, El Segundo, CA 90245
