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Builds and maintains enterprise data products, pipelines, transformations, curated datasets, and scalable data storage solutions. Ensures data quality, governance, metadata, lineage, access, and retention across diverse sources. Collaborates with product, engineering, analytics, data science, and business teams to deliver reliable, reusable, AI-ready data for reporting, automation, machine learning, and GenAI use cases. Responsibilities include ETL/ELT development, data modeling, distributed cloud processing, monitoring, troubleshooting, testing, documentation, and Agile delivery.

Leads the design, development, deployment, and maintenance of scalable data platforms and pipelines. Builds governed data products, models, transformations, and integrations across diverse sources and cloud environments. Ensures data quality, integrity, metadata, lineage, performance, monitoring, and documentation. Partners with product, data science, architecture, and business teams to deliver analytics, reporting, APIs, automation, and AI-ready datasets. Coaches less experienced team members and works within Agile delivery teams.

Leads the design, development, deployment, and maintenance of enterprise data platforms and scalable pipelines. Builds governed data products, data models, ETL/ELT processes, cloud-based storage and processing solutions, and data quality monitoring. Partners with product managers, data scientists, engineers, and business stakeholders to deliver analytics, reporting, APIs, automation, and AI-ready datasets. Optimizes performance, documents solutions, supports Agile delivery, troubleshoots pipelines, and mentors less experienced team members.

Develops and maintains enterprise data products, including scalable data pipelines, ETL/ELT processes, transformations, curated datasets, and distributed cloud-based storage solutions. Implements data quality monitoring, governance, metadata, lineage, access, and retention practices. Collaborates with product, engineering, analytics, and business stakeholders to deliver reliable, reusable, and AI-ready data products. Supports data modeling, testing, troubleshooting, documentation, and Agile development.

Builds and maintains enterprise data products, pipelines, transformations, curated datasets, and scalable data storage solutions. Ensures data quality, governance, metadata, lineage, security, and reliable access for analytics, automation, machine learning, and GenAI use cases. Collaborates with product, engineering, data science, analytics, and business teams to translate requirements into maintainable, reusable technical solutions. Supports testing, monitoring, troubleshooting, documentation, and agile delivery of cloud-based data platforms.

Develops and maintains enterprise data products, scalable data pipelines, ETL/ELT processes, data transformations, storage architectures, and curated datasets. Ensures data quality, governance, metadata, lineage, security, and reliable self-service access. Collaborates with product, engineering, analytics, business, and data science teams to deliver analytics-, AI-, and GenAI-ready data solutions using cloud and distributed technologies.

Builds and maintains enterprise data products, pipelines, transformations, curated datasets, and scalable cloud-based data platforms. Ensures data quality, governance, metadata, lineage, security, and reliable access for analytics, reporting, automation, machine learning, and GenAI use cases. Collaborates with product, engineering, data science, analytics, IT, and business stakeholders to translate requirements into maintainable technical solutions. Supports distributed storage and processing systems, testing, monitoring, troubleshooting, and Agile delivery practices.

Leads the design, development, deployment, and maintenance of scalable data platforms and pipelines. Builds governed, discoverable data products and reliable ETL/ELT workflows from diverse sources. Designs data models, optimizes databases, monitors data quality, and supports analytics, APIs, automation, AI/ML, and GenAI use cases. Collaborates with cross-functional stakeholders, translates requirements into technical solutions, applies Agile and DevOps practices, and mentors less experienced engineers.

Leads business process and internal control reviews, identifies risks and control gaps, and drives remediation and governance improvements. Maintains control documentation, partners with business leaders, finance teams, auditors, and policy teams, and embeds controls in system implementations. Provides training and guidance on risk management and compliance while coaching internal controls staff. Requires accounting expertise, US GAAP knowledge, professional certification, and significant supervisory experience.

Perform monthly and annual balance sheet reconciliations (AR, AP, Cash), prepare basic journal entries, analyze GL and reconciliations, resolve and escalate open items, support month-end close and SOX/internal audit compliance, and assist with financial reporting and ad hoc requests to improve accounting processes and centralization.