Data Pipelie Delivery- Senior Analyst

Overview

Data Pipeline Delivery Analyst role at MUFG's Technology division, focused on designing, developing and modernizing enterprise data pipelines with Snowflake, Python, SQL and AI-assisted development practices.

What you'll do

• Lead the analysis, validation, cleansing, enrichment and preparation of data from multiple sources for reporting, analytics, operational and AI-enabled use cases.
• Design, develop, test, optimize and monitor AI-assisted data ingestion pipelines delivering structured and unstructured data into enterprise platforms, with emphasis on Snowflake-based environments.
• Apply AI-assisted pipeline development approaches to accelerate Python-based data preparation, transformation logic, orchestration support, code generation, troubleshooting and creation of model-ready datasets for generative AI and analytics workflows.
• Define and maintain technical documentation covering data mappings, transformation rules, lineage, quality controls, operational procedures, runbooks and production support processes.
• Develop advanced SQL queries, data profiling routines, reconciliation controls and exception handling processes to identify data issues, anomalies, performance gaps and improvement opportunities.
• Partner with reporting and analytics teams to design and maintain dashboards, reports and data products providing timely, trusted insights to business and technology stakeholders.
• Own or contribute to testing strategies for ETL/ELT pipelines, including test planning, automation opportunities, defect management, performance validation and release readiness documentation.
• Embed data governance, metadata management, data quality, privacy, security and auditability standards into pipeline design and day-to-day delivery.
• Collaborate with cross-functional teams to interpret business requirements, shape technical solutions, estimate delivery effort, manage dependencies and translate requirements into scalable pipeline and data product deliverables.
• Monitor production data jobs, triage issues, analyze logs and data exceptions, coordinate remediation and support continuous improvement of operational stability and reliability.
• Maintain high-quality delivery documentation in Jira, Confluence and Microsoft Office to support auditability, transparency, knowledge sharing and stakeholder communication.
• Provide technical guidance to junior team members and stay current with emerging AI, Snowflake, data engineering and analytics technologies to drive practical improvements in delivery practices.

What you'll need

• 8-10 years of overall experience, with 5+ most recent years in data engineering, data warehousing, business intelligence, analytics engineering, technology delivery or related enterprise data roles.
• Strong hands-on knowledge of SQL, data analysis, relational database concepts, dimensional modeling and enterprise data warehousing patterns.
• Advanced programming or scripting experience using Python, with practical exposure to PySpark, Shell Scripting, APIs, reusable utilities and automation.
• Proven experience designing and implementing ETL/ELT pipelines, AI-assisted pipeline development practices, ingestion frameworks, transformation logic, data quality controls and production-ready data workflows.
• Hands-on experience with AI technologies, including machine learning, generative AI, prompt-based tools, vector databases, model-ready data preparation and retrieval-augmented generation concepts.
• Hands-on experience with Snowflake and the AWS cloud technology stack; experience building, optimizing and supporting Python-based data pipelines in cloud data platforms using AI-assisted development tools.
• Strong understanding of data quality, lineage, privacy, controls, auditability and secure data handling in regulated enterprise environments.
• Strong analytical thinking, problem-solving capability, attention to detail and ability to operate independently across multiple priorities.
• Experience with workflow orchestration, batch job monitoring, scheduling and production support tools such as Autosys, Airflow or similar platforms.
• Bachelor's degree in computer science, information systems, data analytics, engineering, mathematics, statistics, business, finance or a related field.

Nice to have

• Familiarity with AI governance practices and controls.
• Relevant certifications in Snowflake, cloud platforms, AI and ML.
• Master's degree or relevant advanced certifications in data engineering, cloud platforms, Snowflake, AI or analytics.

Details

• Location: Bangalore, India (Bengaluru Branch).
• Experience level: 5-8 years as stated in the job header.