Sr. Director Data Platform Engineering & Operations

San Diego, CA

The Sr. Director Data Platform Engineering & Operations is a critical leadership role at SIE, responsible for driving innovation and scalability across the company’s data and AI platform ecosystem. This role oversees platforms including Data Infrastructure (Streaming, Ingestion, Warehouse, and Data Ocean), Experimentation and Audience Platforms, and Governance & Data Observability tools.

In this role, you will ensure SIE’s platforms process massive volumes of data, delivering insights that enhance Player, Creator, Publisher, and Enterprise experiences. By enabling data-driven decisions at scale, you will drive the future of personalized gaming, efficient operations, and enterprise productivity through advanced AI and machine learning technologies.

As a strategic leader, you will define and execute the vision for SIE’s data and AI platform ecosystem, ensuring scalable solutions that support key business objectives across gaming, content creation, and enterprise operations. Reporting to the VP of Data & AI, you will lead global teams of engineers and experts to build platforms that democratize data and transform decision-making across the company.  Priority consideration will be given to candidates with proven experience in a previous or current Sr. Director level role. 

This highly cross-functional role works closely with senior leadership in engineering, product, and business to align the platform ecosystem with the organization’s strategic goals.

Key Responsibilities:

Strategic Leadership:

• Define the long-term vision for SIE’s Data and AI Platform ecosystem, aligning with business goals and driving value across Player, Creator, Publisher, and Enterprise touchpoints.
• Lead the development of platforms that process large-scale, real-time data from millions of users, delivering insights to enhance gaming experiences, content creation, and enterprise productivity.
• Build scalable platforms for personalized player experiences, content creation tools, and enterprise efficiency, optimizing performance and cost-effectiveness.

Platform Development & Operations:

• Provide thought leadership in the design, architecture, and execution of the platform ecosystem, ensuring innovation and seamless integration with SIE’s global gaming services and enterprise operations.
• Ensure platforms are optimized for performance, scalability, and reliability, processing billions of data points daily across Player, Creator, Publisher, and Enterprise activities.
• Champion operational excellence by driving continuous improvements in platform cost efficiency, performance, and security to support SIE’s global user base.

Cross-functional Collaboration:

• Collaborate with senior leaders to deliver data and AI solutions that drive value across gaming, content creation, and enterprise operations.
• Work with teams to ensure data platforms improve engagement, content creation, monetization, and efficiency.
• Ensure compliance with privacy, security, and regulatory requirements while supporting scalable data operations.

Innovation & Efficiency:

• Lead efforts to optimize platform performance, reduce costs, and improve data accessibility across gaming and enterprise operations.
• Implement innovative solutions to scale data operations and maximize value from Player, Creator, Publisher, and Enterprise data.
• Drive AI/ML adoption to enhance gaming experiences, content discovery, operational efficiency, and enterprise workflows.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.

Experience:

Technical Expertise:

• 15+ years of experience in data engineering, platform engineering, or related fields, with deep expertise in designing and building distributed data systems and large-scale data warehouses.
• Proven track record of architecting platforms capable of processing petabytes of data and supporting the real-time ingestion and processing of billions of data points daily across gaming and enterprise domains.
• Extensive experience in building and scaling cloud-native architectures (AWS, Azure, GCP) for data platforms, with a strong focus on high availability, fault tolerance, and cost-efficiency.
• Demonstrated success in growing and evolving data platforms to meet the needs of a rapidly scaling business, ensuring data-driven decisions are made at all levels of the organization.
• Extensive experience with Kafka for data streaming and real-time data ingestion.
• Strong hands-on knowledge of Databricks and Snowflake for scalable data engineering, analytics, and cloud data warehousing.
• Proven experience making buy vs. build decisions, assessing in-house development versus integrating third-party platforms based on cost, scalability, and business needs.
• Expertise with Data Governance tools such as Alation and Collibra for managing data catalogs, compliance, and data quality.
• Knowledge and experience with Data Observability tools to monitor data pipelines and ensure data accuracy, reliability, and transparency.
• Experience with experimentation platforms such as Optimizely, Statsig, and LaunchDarkly, with a focus on A/B testing and feature management.
• Expertise in AI/ML platforms like AWS SageMaker and Databricks MLflow for machine learning model development, deployment, and MLOps practices.

Leadership & Strategic Skills:

• Proven leadership (in a prior Sr. Director level role strongly preferred) building and leading high-performing global engineering teams, balancing short-term execution with long-term strategic growth.
• Strong strategic mindset, translating business objectives into scalable technical solutions that deliver value across the organization.
• Excellent communication and collaboration skills, driving impactful solutions across engineering, product, and business teams.

#LI-GD1

Senior AI Data Engineer (Full-time)

Remote in CA, TX, NC, WA, ID, NV, AZ, CO, KS, AR, LA, AL, GA, FL, SC, TN, VA, MD, NJ, DE, IL, WI, MI, OH, MA, PA, NH, CT

Cortica is looking for a Senior AI Data Engineer to join its growing team!

The Senior AI Data Engineer will serve as both architect and builder of our data ecosystem. Every initiative will follow a complete engineering lifecycle: gathering stakeholder requirements, designing the solution, building and testing it, and shipping it to production. This role will work across data lakes, analytics pipelines, and lightweight application development— the multi-disciplinary data equivalent of a full-stack developer.

The Senior AI Data Engineer will work closely with the data science, finance, and clinical operations teams to design intelligent, automated data solutions that power care decisions, financial planning, and operational efficiency. AI augmentation is not optional — it is the standard working mode.

Cortica is a rapidly growing healthcare company pioneering the most effective treatment methods for children with neurodevelopmental differences. Our mission is to design and deliver life-changing care – one child, one family, one community at a time. Ultimately, we envision a world that cultivates the full potential of every child. At Cortica, every team member is instrumental in helping us achieve our mission!

Our culture and values guide how we work and treat one another. Cortica celebrates diversity and fosters an inclusive environment, seeking ideas and opinions from everyone on the team. We safeguard equal rights and respect for all individuals, regardless of race, color, religion, sex, national origin, age, disability, creed, genetic information, sexual orientation, gender identity or expression, ancestry, veteran status or other applicable, legally protected characteristics. All Cortica employment decisions are made based on an individual’s qualifications and ability to successfully perform the job responsibilities.

What will you do?

Full Lifecycle Project Ownership:

• Engage stakeholders directly to gather, clarify, and document project requirements.
• Translate requirements into architected data solutions: choose the right storage, pipeline, modeling, and delivery approach for each problem.
• Own testing end-to-end — unit tests, data quality checks, reconciliation, and integration tests before anything reaches production.
• Deploy solutions to production and monitor post-deployment health, iterating rapidly based on real-world feedback.

AI-First Data Engineering: 

• Run parallel AI coding sessions (Claude Code, Cursor, Codex) across different facets of a pipeline simultaneously — orchestrate, verify, and integrate the outputs.
• Build and maintain context files (CLAUDE.md equivalents) for data projects that encode schema conventions, pipeline patterns, and institutional knowledge — making every future AI session smarter.
• Design verification loops: automated data quality checks, dbt tests, CI hooks, and pipeline monitors that give AI agents concrete feedback on correctness. • Build MCP (Model Context Protocol) or equivalent integrations to connect AI agents directly to Snowflake, Amazon Athena, Postgresql, MySql, Power BI APIs, Salesforce, and internal tooling.
• Prefer frontier models for complex architectural decisions and rely on AI acceleration to dramatically increase engineering throughput.

Data Platform & Pipeline Engineering:

• Design and build complex, reliable data pipelines ingesting from AWS, Azure, Salesforce, MuleSoft, and multiple third-party APIs into our AWS Data Lake and Snowflake warehouse.
• Implement and evolve data models using Kimball methodology to support financial, operational, and clinical analytics.
• Optimize pipeline performance, manage data quality, and perform root-cause analysis on data anomalies — internal and external. • Develop and maintain orchestration workflows in Python, and AWS Glue.
• Continuously evolve the data schema as business and engineering requirements change.

Analytics & Reporting Enablement:

• Build and support Power BI data models and reports; empower analytics team members to self-serve on a reliable data foundation.
• Work with data analysts and data scientists to build reusable, well-documented pipeline components they can extend independently.
• Deliver data products that drive clinical care decisions, financial planning, and operational performance improvements.

Application Development:

• Build lightweight internal data applications and tooling where needed; data entry interfaces, operational dashboards, automation scripts that bridge the gap between data pipelines and end users.
• Design for agentic workflows: build AI-powered data tools accessible via web interfaces or Slack that surface insights proactively.
• Integrate with Salesforce Health Cloud and other platforms using APIs and event-driven patterns.

Security, Governance & Collaboration: 

• Ensure data security and HIPAA compliance in all pipeline and application work. Partner with IT to enforce data governance standards.
• Document decisions, tradeoffs, and architecture clearly so that future engineers (and AI agents) can build on your work effectively.
• Collaborate across IT, finance, clinical operations, and data science — acting as the connective tissue between data infrastructure and business outcomes.

We’d love to hear from you if:

• You have 5+ years of hands-on data engineering experience, including building and operating production data pipelines.
• You have expert-level Python skills for ETL, pipeline orchestration, and automation.
• You possess deep SQL proficiency — query optimization, data modeling, stored procedures.
• You bring 2+ years’ experience working with AI first development workflows.
• You bring 4+ years’ experience with the following AWS (S3, Glue, Lambda, Redshift), and/or Azure big data services.
• You have 1+ year of experience with Snowflake.
• You have 2+ years of experience with orchestration frameworks.
• You have 2+ years of Salesforce experience with Apex and configurations.
• You’re experienced with Kimball dimensional modeling — you've built star schemas and conformed dimensions in production.
• You have Power BI (or equivalent BI tool) experience — data model design and report development.
• You have API integration experience — REST, GraphQL, event streaming (Kafka, Kinesis, or similar).
• You possess application development literacy — comfortable building lightweight web tooling (Python/Flask, Node, or similar) to complement data products.
• You reside in one of the following states: CA, TX, NC, WA, ID, NV, AZ, CO, KS, AR, LA, AL, GA, FL, SC, TN, VA, MD, NJ, DE, IL, WI, MI, OH, MA, PA, NH, CT

Your Compensation & Benefits

Cortica cares deeply about the well-being of each member of our team, and we have created a passionate, caring, and growth-minded culture that helps teammates thrive! As a Cortica teammate, we’ll support your well-being through medical, dental, and vision insurance, a 401(k) plan with company matching and rapid vesting, paid holidays and wellness days, life insurance, disability insurance options, tuition reimbursements for professional development and continuing education, and referral bonuses. We value you and the experience you bring to your role, and are proud to provide you with a compensation and benefits package designed to enhance all aspects of your life.

The base pay range for this opening is $160,000 to $200,000. According to your skill level, relevant experience, education level, and location, you will receive compensation that fits appropriately within the range. EOE. This posting is not meant to be an exhaustive list of the role and its duties.

Privacy Notice 
Cortica is committed to protecting your personal information in compliance with applicable federal and state laws. Please review our Privacy Notice to understand how your data is collected, used, and protected. 

E-Verify Participation 
This employer participates in E-Verify. Click here to view the E-Verify Poster and your Right to Work. 
Este empleador participa en E-Verify. Este empleador participa en E-Verify. Haga clic aquí para ver el cartel de E-Verify y su derecho a trabajar. 

#LI-NF1

#LI-Remote

Senior AI Data Engineer (Full-time)

Remote in CA, TX, NC, WA, ID, NV, AZ, CO, KS, AR, LA, AL, GA, FL, SC, TN, VA, MD, NJ, DE, IL, WI, MI, OH, MA, PA, NH, CT

Cortica is looking for a Senior AI Data Engineer to join its growing team!

The Senior AI Data Engineer will serve as both architect and builder of our data ecosystem. Every initiative will follow a complete engineering lifecycle: gathering stakeholder requirements, designing the solution, building and testing it, and shipping it to production. This role will work across data lakes, analytics pipelines, and lightweight application development— the multi-disciplinary data equivalent of a full-stack developer.

The Senior AI Data Engineer will work closely with the data science, finance, and clinical operations teams to design intelligent, automated data solutions that power care decisions, financial planning, and operational efficiency. AI augmentation is not optional — it is the standard working mode.

Cortica is a rapidly growing healthcare company pioneering the most effective treatment methods for children with neurodevelopmental differences. Our mission is to design and deliver life-changing care – one child, one family, one community at a time. Ultimately, we envision a world that cultivates the full potential of every child. At Cortica, every team member is instrumental in helping us achieve our mission!

Our culture and values guide how we work and treat one another. Cortica celebrates diversity and fosters an inclusive environment, seeking ideas and opinions from everyone on the team. We safeguard equal rights and respect for all individuals, regardless of race, color, religion, sex, national origin, age, disability, creed, genetic information, sexual orientation, gender identity or expression, ancestry, veteran status or other applicable, legally protected characteristics. All Cortica employment decisions are made based on an individual’s qualifications and ability to successfully perform the job responsibilities.

What will you do?

Full Lifecycle Project Ownership:

• Engage stakeholders directly to gather, clarify, and document project requirements.
• Translate requirements into architected data solutions: choose the right storage, pipeline, modeling, and delivery approach for each problem.
• Own testing end-to-end — unit tests, data quality checks, reconciliation, and integration tests before anything reaches production.
• Deploy solutions to production and monitor post-deployment health, iterating rapidly based on real-world feedback.

AI-First Data Engineering: 

• Run parallel AI coding sessions (Claude Code, Cursor, Codex) across different facets of a pipeline simultaneously — orchestrate, verify, and integrate the outputs.
• Build and maintain context files (CLAUDE.md equivalents) for data projects that encode schema conventions, pipeline patterns, and institutional knowledge — making every future AI session smarter.
• Design verification loops: automated data quality checks, dbt tests, CI hooks, and pipeline monitors that give AI agents concrete feedback on correctness. • Build MCP (Model Context Protocol) or equivalent integrations to connect AI agents directly to Snowflake, Amazon Athena, Postgresql, MySql, Power BI APIs, Salesforce, and internal tooling.
• Prefer frontier models for complex architectural decisions and rely on AI acceleration to dramatically increase engineering throughput.

Data Platform & Pipeline Engineering:

• Design and build complex, reliable data pipelines ingesting from AWS, Azure, Salesforce, MuleSoft, and multiple third-party APIs into our AWS Data Lake and Snowflake warehouse.
• Implement and evolve data models using Kimball methodology to support financial, operational, and clinical analytics.
• Optimize pipeline performance, manage data quality, and perform root-cause analysis on data anomalies — internal and external. • Develop and maintain orchestration workflows in Python, and AWS Glue.
• Continuously evolve the data schema as business and engineering requirements change.

Analytics & Reporting Enablement:

• Build and support Power BI data models and reports; empower analytics team members to self-serve on a reliable data foundation.
• Work with data analysts and data scientists to build reusable, well-documented pipeline components they can extend independently.
• Deliver data products that drive clinical care decisions, financial planning, and operational performance improvements.

Application Development:

• Build lightweight internal data applications and tooling where needed; data entry interfaces, operational dashboards, automation scripts that bridge the gap between data pipelines and end users.
• Design for agentic workflows: build AI-powered data tools accessible via web interfaces or Slack that surface insights proactively.
• Integrate with Salesforce Health Cloud and other platforms using APIs and event-driven patterns.

Security, Governance & Collaboration: 

• Ensure data security and HIPAA compliance in all pipeline and application work. Partner with IT to enforce data governance standards.
• Document decisions, tradeoffs, and architecture clearly so that future engineers (and AI agents) can build on your work effectively.
• Collaborate across IT, finance, clinical operations, and data science — acting as the connective tissue between data infrastructure and business outcomes.

We’d love to hear from you if:

• You have 5+ years of hands-on data engineering experience, including building and operating production data pipelines.
• You have expert-level Python skills for ETL, pipeline orchestration, and automation.
• You possess deep SQL proficiency — query optimization, data modeling, stored procedures.
• You bring 2+ years’ experience working with AI first development workflows.
• You bring 4+ years’ experience with the following AWS (S3, Glue, Lambda, Redshift), and/or Azure big data services.
• You have 1+ year of experience with Snowflake.
• You have 2+ years of experience with orchestration frameworks.
• You have 2+ years of Salesforce experience with Apex and configurations.
• You’re experienced with Kimball dimensional modeling — you've built star schemas and conformed dimensions in production.
• You have Power BI (or equivalent BI tool) experience — data model design and report development.
• You have API integration experience — REST, GraphQL, event streaming (Kafka, Kinesis, or similar).
• You possess application development literacy — comfortable building lightweight web tooling (Python/Flask, Node, or similar) to complement data products.
• You reside in one of the following states: CA, TX, NC, WA, ID, NV, AZ, CO, KS, AR, LA, AL, GA, FL, SC, TN, VA, MD, NJ, DE, IL, WI, MI, OH, MA, PA, NH, CT

Your Compensation & Benefits

Cortica cares deeply about the well-being of each member of our team, and we have created a passionate, caring, and growth-minded culture that helps teammates thrive! As a Cortica teammate, we’ll support your well-being through medical, dental, and vision insurance, a 401(k) plan with company matching and rapid vesting, paid holidays and wellness days, life insurance, disability insurance options, tuition reimbursements for professional development and continuing education, and referral bonuses. We value you and the experience you bring to your role, and are proud to provide you with a compensation and benefits package designed to enhance all aspects of your life.

The base pay range for this opening is $160,000 to $200,000. According to your skill level, relevant experience, education level, and location, you will receive compensation that fits appropriately within the range. EOE. This posting is not meant to be an exhaustive list of the role and its duties.

Privacy Notice 
Cortica is committed to protecting your personal information in compliance with applicable federal and state laws. Please review our Privacy Notice to understand how your data is collected, used, and protected. 

E-Verify Participation 
This employer participates in E-Verify. Click here to view the E-Verify Poster and your Right to Work. 
Este empleador participa en E-Verify. Este empleador participa en E-Verify. Haga clic aquí para ver el cartel de E-Verify y su derecho a trabajar. 

#LI-NF1

#LI-Remote

What The Role Is

We are seeking a talented Senior Data Engineer to design, build, and maintain our data infrastructure supporting mission-critical energy operations. You'll work at the intersection of renewable energy and data, developing pipelines that process everything from real-time asset performance data to complex trading and risk analytics. This hybrid role offers the opportunity to make a direct impact on clean energy operations while working with a cutting-edge data stack including Snowflake, Dagster, dbt, Modal, and GitLab.

What You'll Be Doing

Analytics Infrastructure & Data Warehouse Management

• Design, deploy, and maintain scalable data infrastructure to support enterprise analytics and reporting needs
• Manage Snowflake instances, including performance tuning, security configuration, and capacity planning for growing data volumes
• Optimize query performance and resource utilization to control costs and improve processing speed

Data Pipeline Development & Orchestration

• Build and orchestrate complex ETL/ELT workflows using Dagster to ensure reliable, automated data processing for asset management and energy trading
• Develop robust data pipelines that handle high-volume, time-sensitive energy market data and asset generation and performance metrics
• Implement workflow automation and dependency management for critical business operations

Data Transformation & Analytics Support

• Develop and maintain dbt models to transform raw data into business-ready analytical datasets and dimensional models
• Create efficient SQL-based transformations for complex energy market calculations and asset performance metrics
• Support advanced analytics initiatives through proper data preparation and feature engineering

Data Quality & Governance

• Implement comprehensive data validation, testing, and monitoring frameworks to ensure accuracy and consistency across all energy and financial data assets
• Establish data lineage tracking and privacy controls to meet regulatory compliance requirements in the energy sector
• Develop alerting and monitoring systems for data pipelines, including error handling, SLA monitoring, and incident response

CI/CD & DevOps

• Lead continuous integration and deployment initiatives for Dagster and dbt pipelines, and Streamlit/Gradio application deployments to Linux servers
• Implement automated testing and deployment automation for data pipelines and analytics applications
• Manage version control and infrastructure as code practices

Cross-functional Collaboration

• Partner with Analytics Engineers, Data Scientists, and business stakeholders to understand requirements and deliver solutions
• Work closely with asset management and trading groups to ensure real-time data availability for market operations and risk calculations
• Collaborate with credit risk teams to develop data models supporting financial analysis and regulatory reporting
• Translate business requirements into technical solutions and communicate data insights to stakeholders

Documentation & Security

• Create and maintain technical documentation, data dictionaries, and onboarding materials for data assets
• Implement role-based access controls, data encryption, and security best practices across the data stack
• Monitor and optimize cloud infrastructure costs, implement resource allocation strategies, and provide cost forecasting

What You'll Bring

• Experience: 4+ years of hands-on data engineering experience in production environments
• Education: Bachelor's degree in Computer Science, Engineering, or a related field
• Data Orchestration: Proficiency in Dagster for pipeline scheduling, dependency management, and workflow automation; Airflow experience a plus
• Cloud Data Warehousing: Advanced-level Snowflake administration, including virtual warehouses, clustering, security, and cost optimization
• Data Transformation: Proficiency in dbt for data modeling, testing, documentation, and version control of analytical transformations
• Programming: Strong Python and SQL skills for data processing and automation
• CI/CD: 3+ years of experience with continuous integration and continuous deployment practices and tools; proficiency in GitLab CI/CD required (GitHub Actions experience a plus)
• Database Technologies: Advanced SQL skills, database design principles, and experience with multiple database platforms
• Cloud Platforms: Proficiency in AWS/Azure/GCP data services, storage solutions (S3, Azure Blob, GCS), and infrastructure as code
• Data Integration: Experience with APIs, various data connectors, and formats
• Data Security: Understanding of data security best practices, access controls, encryption, and role-based access management
• AI & LLM Proficiency: Practical experience integrating and leveraging large language models (e.g., OpenAI, Anthropic, or open-source models) within data workflows; ability to apply LLMs efficiently and securely, with awareness of data privacy boundaries, prompt injection risks, and responsible AI usage in production environments
• Problem-Solving: Strong analytical and troubleshooting skills with attention to detail
• Communication: Ability to work effectively with both technical and business stakeholders
• Work Style: Comfortable with a hybrid work environment (2-3 days in office); highly autonomous and self-directed with a strong work ethic and growth mindset; exceptional attention to detail; able to take ownership of projects end-to-end with minimal oversight

What Would Be Nice

• Experience in the energy, utilities, or financial services industries
• Knowledge of energy trading concepts, market data, or asset management
• Familiarity with data governance frameworks and regulatory compliance (SOX, GDPR, CCPA)
• Experience with infrastructure as code (Terraform, CloudFormation)

Clearway will not sponsor non-immigrant visas for this position (H-1B, TN, E-3, etc.).

#LI-Hybrid

What The Role Is

We are seeking a talented Senior Data Engineer to design, build, and maintain our data infrastructure supporting mission-critical energy operations. You'll work at the intersection of renewable energy and data, developing pipelines that process everything from real-time asset performance data to complex trading and risk analytics. This hybrid role offers the opportunity to make a direct impact on clean energy operations while working with a cutting-edge data stack including Snowflake, Dagster, dbt, Modal, and GitLab.

What You'll Be Doing

Analytics Infrastructure & Data Warehouse Management

• Design, deploy, and maintain scalable data infrastructure to support enterprise analytics and reporting needs
• Manage Snowflake instances, including performance tuning, security configuration, and capacity planning for growing data volumes
• Optimize query performance and resource utilization to control costs and improve processing speed

Data Pipeline Development & Orchestration

• Build and orchestrate complex ETL/ELT workflows using Dagster to ensure reliable, automated data processing for asset management and energy trading
• Develop robust data pipelines that handle high-volume, time-sensitive energy market data and asset generation and performance metrics
• Implement workflow automation and dependency management for critical business operations

Data Transformation & Analytics Support

• Develop and maintain dbt models to transform raw data into business-ready analytical datasets and dimensional models
• Create efficient SQL-based transformations for complex energy market calculations and asset performance metrics
• Support advanced analytics initiatives through proper data preparation and feature engineering

Data Quality & Governance

• Implement comprehensive data validation, testing, and monitoring frameworks to ensure accuracy and consistency across all energy and financial data assets
• Establish data lineage tracking and privacy controls to meet regulatory compliance requirements in the energy sector
• Develop alerting and monitoring systems for data pipelines, including error handling, SLA monitoring, and incident response

CI/CD & DevOps

• Lead continuous integration and deployment initiatives for Dagster and dbt pipelines, and Streamlit/Gradio application deployments to Linux servers
• Implement automated testing and deployment automation for data pipelines and analytics applications
• Manage version control and infrastructure as code practices

Cross-functional Collaboration

• Partner with Analytics Engineers, Data Scientists, and business stakeholders to understand requirements and deliver solutions
• Work closely with asset management and trading groups to ensure real-time data availability for market operations and risk calculations
• Collaborate with credit risk teams to develop data models supporting financial analysis and regulatory reporting
• Translate business requirements into technical solutions and communicate data insights to stakeholders

Documentation & Security

• Create and maintain technical documentation, data dictionaries, and onboarding materials for data assets
• Implement role-based access controls, data encryption, and security best practices across the data stack
• Monitor and optimize cloud infrastructure costs, implement resource allocation strategies, and provide cost forecasting

What You'll Bring

• Experience: 4+ years of hands-on data engineering experience in production environments
• Education: Bachelor's degree in Computer Science, Engineering, or a related field
• Data Orchestration: Proficiency in Dagster for pipeline scheduling, dependency management, and workflow automation; Airflow experience a plus
• Cloud Data Warehousing: Advanced-level Snowflake administration, including virtual warehouses, clustering, security, and cost optimization
• Data Transformation: Proficiency in dbt for data modeling, testing, documentation, and version control of analytical transformations
• Programming: Strong Python and SQL skills for data processing and automation
• CI/CD: 3+ years of experience with continuous integration and continuous deployment practices and tools; proficiency in GitLab CI/CD required (GitHub Actions experience a plus)
• Database Technologies: Advanced SQL skills, database design principles, and experience with multiple database platforms
• Cloud Platforms: Proficiency in AWS/Azure/GCP data services, storage solutions (S3, Azure Blob, GCS), and infrastructure as code
• Data Integration: Experience with APIs, various data connectors, and formats
• Data Security: Understanding of data security best practices, access controls, encryption, and role-based access management
• AI & LLM Proficiency: Practical experience integrating and leveraging large language models (e.g., OpenAI, Anthropic, or open-source models) within data workflows; ability to apply LLMs efficiently and securely, with awareness of data privacy boundaries, prompt injection risks, and responsible AI usage in production environments
• Problem-Solving: Strong analytical and troubleshooting skills with attention to detail
• Communication: Ability to work effectively with both technical and business stakeholders
• Work Style: Comfortable with a hybrid work environment (2-3 days in office); highly autonomous and self-directed with a strong work ethic and growth mindset; exceptional attention to detail; able to take ownership of projects end-to-end with minimal oversight

What Would Be Nice

• Experience in the energy, utilities, or financial services industries
• Knowledge of energy trading concepts, market data, or asset management
• Familiarity with data governance frameworks and regulatory compliance (SOX, GDPR, CCPA)
• Experience with infrastructure as code (Terraform, CloudFormation)

Clearway will not sponsor non-immigrant visas for this position (H-1B, TN, E-3, etc.).

#LI-Hybrid

What The Role Is

We are seeking a talented Senior Data Engineer to design, build, and maintain our data infrastructure supporting mission-critical energy operations. You'll work at the intersection of renewable energy and data, developing pipelines that process everything from real-time asset performance data to complex trading and risk analytics. This hybrid role offers the opportunity to make a direct impact on clean energy operations while working with a cutting-edge data stack including Snowflake, Dagster, dbt, Modal, and GitLab.

What You'll Be Doing

Analytics Infrastructure & Data Warehouse Management

• Design, deploy, and maintain scalable data infrastructure to support enterprise analytics and reporting needs
• Manage Snowflake instances, including performance tuning, security configuration, and capacity planning for growing data volumes
• Optimize query performance and resource utilization to control costs and improve processing speed

Data Pipeline Development & Orchestration

• Build and orchestrate complex ETL/ELT workflows using Dagster to ensure reliable, automated data processing for asset management and energy trading
• Develop robust data pipelines that handle high-volume, time-sensitive energy market data and asset generation and performance metrics
• Implement workflow automation and dependency management for critical business operations

Data Transformation & Analytics Support

• Develop and maintain dbt models to transform raw data into business-ready analytical datasets and dimensional models
• Create efficient SQL-based transformations for complex energy market calculations and asset performance metrics
• Support advanced analytics initiatives through proper data preparation and feature engineering

Data Quality & Governance

• Implement comprehensive data validation, testing, and monitoring frameworks to ensure accuracy and consistency across all energy and financial data assets
• Establish data lineage tracking and privacy controls to meet regulatory compliance requirements in the energy sector
• Develop alerting and monitoring systems for data pipelines, including error handling, SLA monitoring, and incident response

CI/CD & DevOps

• Lead continuous integration and deployment initiatives for Dagster and dbt pipelines, and Streamlit/Gradio application deployments to Linux servers
• Implement automated testing and deployment automation for data pipelines and analytics applications
• Manage version control and infrastructure as code practices

Cross-functional Collaboration

• Partner with Analytics Engineers, Data Scientists, and business stakeholders to understand requirements and deliver solutions
• Work closely with asset management and trading groups to ensure real-time data availability for market operations and risk calculations
• Collaborate with credit risk teams to develop data models supporting financial analysis and regulatory reporting
• Translate business requirements into technical solutions and communicate data insights to stakeholders

Documentation & Security

• Create and maintain technical documentation, data dictionaries, and onboarding materials for data assets
• Implement role-based access controls, data encryption, and security best practices across the data stack
• Monitor and optimize cloud infrastructure costs, implement resource allocation strategies, and provide cost forecasting

What You'll Bring

• Experience: 4+ years of hands-on data engineering experience in production environments
• Education: Bachelor's degree in Computer Science, Engineering, or a related field
• Data Orchestration: Proficiency in Dagster for pipeline scheduling, dependency management, and workflow automation; Airflow experience a plus
• Cloud Data Warehousing: Advanced-level Snowflake administration, including virtual warehouses, clustering, security, and cost optimization
• Data Transformation: Proficiency in dbt for data modeling, testing, documentation, and version control of analytical transformations
• Programming: Strong Python and SQL skills for data processing and automation
• CI/CD: 3+ years of experience with continuous integration and continuous deployment practices and tools; proficiency in GitLab CI/CD required (GitHub Actions experience a plus)
• Database Technologies: Advanced SQL skills, database design principles, and experience with multiple database platforms
• Cloud Platforms: Proficiency in AWS/Azure/GCP data services, storage solutions (S3, Azure Blob, GCS), and infrastructure as code
• Data Integration: Experience with APIs, various data connectors, and formats
• Data Security: Understanding of data security best practices, access controls, encryption, and role-based access management
• AI & LLM Proficiency: Practical experience integrating and leveraging large language models (e.g., OpenAI, Anthropic, or open-source models) within data workflows; ability to apply LLMs efficiently and securely, with awareness of data privacy boundaries, prompt injection risks, and responsible AI usage in production environments
• Problem-Solving: Strong analytical and troubleshooting skills with attention to detail
• Communication: Ability to work effectively with both technical and business stakeholders
• Work Style: Comfortable with a hybrid work environment (2-3 days in office); highly autonomous and self-directed with a strong work ethic and growth mindset; exceptional attention to detail; able to take ownership of projects end-to-end with minimal oversight

What Would Be Nice

• Experience in the energy, utilities, or financial services industries
• Knowledge of energy trading concepts, market data, or asset management
• Familiarity with data governance frameworks and regulatory compliance (SOX, GDPR, CCPA)
• Experience with infrastructure as code (Terraform, CloudFormation)

Clearway will not sponsor non-immigrant visas for this position (H-1B, TN, E-3, etc.).

#LI-Hybrid

Brain Corp is a San Diego, California, USA-based AI company creating transformative core technology for the robotics industry. Our purpose is to create autonomous technology that helps the real world work better. Brain's robotic and AI solutions help retailers ensure that the right product is on the right shelf at the right price, in a clean environment. Through the BrainOS® Robotics Platform, which powers the largest global fleet of the Autonomous Mobile Robots (AMRs) in operation in commercial public spaces, Brain Corp delivers insightful and efficient automated solutions in both commercial floor cleaning and inventory management, empowering organizations and their employees to achieve more. Brain Corp currently powers more than 30,000 AMRs, representing the largest fleet of its kind in the world. Brain Corp is funded by the SoftBank Vision Fund, Clearbridge, and Qualcomm Ventures.

Named a top workplace by the San Diego Union Tribune and USA today in 2025, we make life-changing impacts through innovation, helping workers globally unlock their abilities in orchestration with intelligent machines.

Position Overview:

As a member of our Software Engineering team, the Software Engineer II, Data Engineering will play a key role in designing and maintaining the data infrastructure that powers the BrainOS platform. This role requires a solid foundation in data engineering concepts and technologies; with experience in building scalable data pipelines and ensuring the integrity and performance of data systems. The Software Engineer II, Data Engineering will work independently on mid-sized projects and collaborate with senior engineers to tackle larger initiatives.

Essential Job Functions:

• Design and Develop Data Pipelines: Implement robust, scalable pipelines for processing structured and unstructured data
• Data Architecture & Modeling: Contribute to the design of complex data models and optimize storage solutions in support of engineering and business objectives
• Optimize Performance and Scalability: Enhance the efficiency and scalability of data pipelines and storage systems by identifying bottlenecks, and configuring cluster resources
• Collaborate and Support: Collaborate with data analysts, data scientists, and other business teams to support data-related technical issues and support their data infrastructure needs
• Data Security & Compliance: Implement security best practices, including encryption and access control policies, while maintaining data integrity and compliance with quality standards
• Incident Management: Monitor and troubleshoot data pipeline failures and reliability issues

Education and/or Work Experience Requirements:

• BS or MS in Computer Science or applicable engineering discipline
• 2-5 years of proven software development experience, with at least 2 of those years focused on data engineering

Required Knowledge, Skills, Abilities, and Other Characteristics:

• Proficiency in SQL as well as one or more programming languages (Python, Go, or TypeScript)
• Experience with data warehousing (BigQuery, Snowflake, Firestore, MySQL, PostgreSQL)
• Familiarity with stream processing frameworks (Apache Beam, Pub/Sub, Spark Streaming)
• Understanding of data governance, security, and compliance best practices
• Strong problem-solving skills and ability to work independently on projects
• Familiarity using Generative AI tools to enhance development workflows, such as code generation, data exploration, and documentation support
• Effective communication skills demonstrated by effective written and verbal communication; with an ability to articulate technical concepts to both technical and non-technical stakeholders

Things that make a difference:

• Experience with machine learning models and data science methodologies
• Experience with Google Cloud and their data ecosystem
• Familiarity with BI tools (e.g., Tableau, Power BI) and data frameworks (e.g., Hadoop, Spark)
• Experience with infrastructure as code (e.g., Terraform, Pulumi) and containerization and orchestration tools (e.g., Docker, Kubernetes)

Physical Demands:

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Essential functions may require maintaining the physical condition necessary for sitting, walking or standing for periods of time; operating a computer and keyboard; use of hands to finger and grasp; talk and hear at normal room levels; visual acuity to determine the accuracy, neatness, and thoroughness of the work assigned or to make general observations of facilities or structures; push or pull up to 20 pounds.

Work Environment:

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. The noise level in the work environment is usually quiet to moderate. Employees are exposed to the typical office environment with computers, printers and telephones.

Salary Range:

The anticipated salary range for candidates who will work in San Diego, California is $130,000. The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to the type and length of experience within the job, type and length of experience within the industry, education, etc. Brain Corp is a multi-state employer and this salary range may not reflect positions that work in other states.

Please note that this position can be based in Princeton, NJ, San Diego, CA, or San Francisco, CA. Acadia's hybrid model requires this role to work in our office three days per week on average.

Position Summary

The Sr. Director, Commercial Advanced Analytics & Data Strategy is a strategic leadership role responsible for defining, building, and scaling the analytics capabilities, data strategy, and governance frameworks that enable commercial decision-making across the organization. This role ensures that high quality data, advanced analytics, and AI enabled insights are seamlessly integrated into commercial strategy, planning, launch execution, and in market optimization.  The Sr. Director serves as a strategic partner cross-functionally, translating business priorities into scalable analytics products and platforms while ensuring governance, compliance, and measurable business impact.

Over time, this role will build and mature commercial advanced analytics and data capabilities, establish fit‑for‑purpose operating models, and define future talent and capability needs to support the evolving business. The role will work closely with Acadia’s AI team, which provides shared AI expertise across Commercial and R&D, as well as with IT teams responsible for enterprise data, infrastructure, and platform enablement.

Primary Responsibilities

Commercial Analytics Strategy & Leadership

• Partner with Commercial leadership to define the advance analytics vision, strategy and initiatives that enables the development of scalable analytics and decision-support capabilities that drive business outcomes

• Lead and govern advanced analytics projects, predictive analytics, and AI/machine learning solutions  supporting brand strategy, launch planning, patient support, segmentation, targeting, omnichannel optimization, and sales effectiveness.

• Enable AI-driven commercial use cases such as next-best-action, customer engagement optimization, automated forecasting, and scenario planning.

• Balance innovation with rigor by ensuring analytics solutions are interpretable, validated, and compliant with internal and external requirements including privacy laws

• Translate commercial business questions into analytics use cases, models, and decision frameworks.

• Ensure analytics outputs and insights are actionable, adopted, and embedded into commercial planning, existing workflows, processes, systems and demonstrate measurable outcomes.

• Act as a trusted advisor to Commercial leadership, influencing decisions through data-driven insights

• Partner with the Enterprise AI team to identify, prioritize, and scale high-value AI and advanced analytic capabilities, solutions and governance.

Data Strategy, Governance and Cross-Functional Enablement Leadership

• Establish commercial data strategy to support the organization in achieving its business objectives. This includes leading the acquisition, implementation, and evolution of the commercial data assets, including syndicated claims, EMR, prescription, HUB/SP/Partner, promotional, and digital data.

• Partner cross-functionally with Enterprise Data, IT, and infrastructure teams to enable scalable data platforms, data pipelines, and tools that support analytics, AI, and self-service insights.

• Oversee vendor selection and management for data sources, analytics tools, and platforms.

• Establish governance frameworks for data access, analytics validation, and model lifecycle management.

• Collaborate with legal/compliance teams to mitigate risk and ensure compliance with HIPAA, GDPR, CCPA, and internal data privacy and security policies.

• Partner with IT data and infrastructure teams to align commercial analytics needs with enterprise architecture, platform standards, security requirements, and long-term data strategy.

Leadership & Communication

• Serve as a bridge between business stakeholders and technical teams, ensuring clarity of requirements and outcomes.

• Influence senior executives through concise storytelling, visualization, and business impact measurement.

• Build, lead, retain and mentor a high-performing team and capability in support of advanced analytics, data acquisition, and data governance, while fostering a culture of accountability, continuous improvement, and innovation.

• Assess and evolve organizational capabilities, talent, and ways of working needed to scale commercial advanced analytics over time.

• Other responsibilities as assigned.

Education/Experience/Skills

Bachelor’s degree in data science, statistics, engineering, computer science, or a related field; Advanced degree (MS, PhD, or MBA) preferred.  Targeting 12 years of progressively responsible experience in commercial analytics, data science, or data infrastructure data strategy, or related functions, with significant experience in biotech or pharmaceutical organizations.  An equivalent combination of relevant education and experience may be considered.

Key Skills:

• Advanced analytics, modeling, and visualization tool experience (AI/ML, predictive analytics (Python), SQL, R and PowerBI).

• Experience working with modern data platforms and cloud technologies (e.g., Snowflake, Databricks, DataRobot, Dataiku, AWS, Azure, GCP).

• Deep experience and understanding of commercial datasets, data environments, and data vendors (including Hub, Specialty Pharmacy, patient services, Veeva CRM, syndicated claims, prescriptions, payer, social media/website, Google, Facebook etc.).

• Proven ability to lead cross-functional AI/ML and Analytical initiatives and influence senior stakeholders and to drive adoption of analytic solutions.

• Solid understanding of pharmaceutical commercialization concepts including launches, brand planning, and lifecycle management.

• Demonstrated experience in leading data governance initiatives and processes.

• Demonstrated ability to design and communicate complex systems and analytical solutions to both technical and non-technical audiences, aligning resources and execution to achieve functional and enterprise goals.

• Proven abilities with executive-level communication, data storytelling, and change leadership.

• Demonstrated impact of analytics on commercial strategy, decision making, performance, and ROI.

• Proven ability to lead, coach, and develop talent while building organizational capability in a fast-evolving environment.

• Experience partnering effectively with cross-functional partners and business stakeholders to deliver scalable analytics solutions.

• Ability to balance strategic vision with hands-on prioritization and execution in fast past environment.

Physical Requirements

This role involves regular standing, walking, sitting, and the use of hands for handling or operating equipment. The employee may also need to reach, climb, balance, stoop, kneel, crouch, and maintain visual, verbal, and auditory communication in a standard office environment and while working independently from remote locations. The employee must occasionally lift and/or move up to 20 pounds.  This position requires the ability to travel independently overnight and/or work after hours as required by travel schedules or business needs.

#LI-HYBRID #LI-CA1

At Element Biosciences, we are passionate about our mission to empower the scientific community with more freedom and flexibility to accelerate our collective impact on humanity. We have built a highly efficient product-driven organization where employees can learn, grow, and thrive in a challenging but encouraging environment. We are committed to scientific integrity, collegiality, honesty, objectivity, and openness.

We are seeking an experienced Senior Lead, Enterprise Master Data who will play a pivotal role in defining and driving the enterprise master data governance strategy across material, vendor, and customer domains. This role will own the vision, standards, and execution roadmap for master data to enable scalable operations across Supply Chain, Manufacturing, Finance, and Commercial functions. As a key partner to business and technical leadership, you will ensure master data is accurate, compliant, and aligned to business priorities, while driving cross-functional alignment, system integration, and continuous improvement in a GxP-regulated environment.

This is an incredible opportunity for someone who is passionate about enterprise master data governance and strategy, and enjoys working in a dynamic, fast-paced company. This role will report to the Sr Manager, Business Process and will be an on-site, San Diego based role.

If you possess the following and want to make a meaningful impact, we invite you to explore this role.

Essential Functions and Responsibilities:

• Define and evolve the master data governance strategy and multi-year roadmap across material, vendor, and customer domains
• Establish and govern customer master data aligned to order-to-cash processes (customer onboarding, pricing, billing, invoicing, revenue recognition), including ownership models and decision rights with Commercial and Finance
• Establish and enforce data standards, policies, and decision frameworks to ensure consistency and scalability across PLM, ERP, CRM, and downstream systems
• Serve as the authority for material, vendor, and customer master data, driving cross-functional alignment and leading governance forums to resolve ownership and prioritization decisions
• Drive a single source of truth strategy across systems and business processes
• Own and optimize master data lifecycle and data quality (creation through archival, KPIs, and enterprise-wide remediation)
• Ensure compliance with GDP, SOPs, and ISO standards (ISO 27001, 9001, 13485), supporting audit readiness and regulatory requirements
• Standardize customer master attributes (sales channel, payment terms, VAT/EORI, Incoterms, hierarchies, and account structures) to enable accurate order processing, invoicing, and reporting
• Partner with business and IT leaders to support system implementations, integrations, and transformations, ensuring master data requirements are defined and met
• Drive master data readiness to enable product launches and business scale, while advising leadership on data risks, trade-offs, and investments

Education and Experience:

• Bachelor’s degree in Business, Supply Chain, Operations, or related field with 8+ years of experience in Master Data Management, Data Governance, or Business Systems (biotech, pharma, or medical device experience preferred)
• Strong working knowledge in master data domains and data architecture (material, vendor, customer master; strong understanding of interactions with transactional data across order-to-cash, procure-to-pay, and manufacturing processes)
• Experience designing and operating governance and change management processes (data governance frameworks, controlled data changes, impact assessment, change control in regulated/GxP environments)
• Strong systems and data proficiency (ERP, CRM, PLM integrations; SQL, Snowflake, or similar querying tools; Excel and BI/reporting tools such as Tableau or Power BI)
• Proven ability to lead through influence (cross-functional alignment across Supply Chain, Manufacturing, Finance, Commercial, and IT; ability to translate between technical and business stakeholders)
• Strong analytical and execution skills in a fast-paced environment (root cause analysis, process improvement, high attention to detail)

Physical Requirements:

• Ability to lift up to 20 pounds

Location:

• San Diego – on-site

Travel: 

• Up to 5%

Job Type:

• Full-time, Exempt

Base Compensation Pay Range:

• $119,000 - $156,000

In addition to base compensation noted above, you will be eligible for stock options, discretionary annual bonus, no cost health insurance plans, 401k with company match, and flexible paid time off. 

Please note: Base compensation will depend on multiple factors, including geographic location, qualifications, and experience. 

We foster an environment such that all people are afforded the freedom to pursue their passions without regard to race, color, religion, national or ethnic origin, gender (including pregnancy), sexual orientation, gender identity or expression, age, disability, veteran status or any other characteristics protected by law.

Director Business Systems

San Diego, CA/ remote Pacific Time Zone

At Platform Science, we’re working to connect everything that moves.

Founded in 2015, we are an open IoT platform that partners with innovative fleets, application developers, vehicle manufacturers, and equipment providers in the transportation industry to deliver revolutionary solutions to supply chain professionals across the globe.

Our employees are an engaging, diverse group of people who believe in the power of great ideas. We hire people with different experiences and perspectives to build a company culture that fuels growth through innovation. 

We value thoughtful actions and empathy for others.  We approach challenges with resiliency and creativity, while encouraging transparency because, no matter our backgrounds or responsibilities, we are one team.

About the Role

Title: Director, Business Systems
Department: Business Systems
Reports To: VP of IT
Location: Pacific Time Zone

Position Overview

Platform Science is seeking a seasoned Director Business Systems to lead our global NetSuite and Salesforce ecosystems. This is a hands-on leadership role at the intersection of systems architecture, process optimization, and cross-functional collaboration.

You will own the full lifecycle of our core platforms—from strategy to administration—while leading a global team of administrators and analysts. As the SME across NetSuite and Salesforce, you will drive the Lead-to-Cash process including CPQ, CLM, AR/AP automation, PLM, and billing.

This role combines deep technical execution with executive influence.

Key Responsibilities

Platform Leadership & Architecture

• Serve as primary SME and strategic owner for NetSuite (ERP) and Salesforce (CRM)
• Architect scalable solutions across the Lead-to-Cash lifecycle
• Define platform standards, governance, and integration design patterns
• Translate business needs into technical roadmaps
• Balance short-term delivery with long-term scalability

Team Management & Development

• Lead a global team across NA, LATAM, and EU
• Set performance expectations and coaching plans
• Build a high-accountability, collaborative culture
• Partner with HR and IT leadership on hiring and team scaling

Implementations & Integrations

• Lead end-to-end implementations and enhancements
• Manage integrations (Boomi, Snowflake, Zoom, TalkDesk, etc.)
• Oversee data migration, testing, and deployment
• Drive change management and adoption

Process Optimization

• Improve workflows across Finance, Sales Ops, Supply Chain, and PLM
• Lead business analysis and future-state design
• Ensure audit readiness and compliance
• Build reporting and analytics for leadership insights

Operations & Support

• Own system health, releases, and user administration
• Resolve complex system issues
• Manage vendors and licensing
• Maintain roadmap and backlog prioritization

Required Qualifications

Experience

• 7+ years in Business Systems or IT
• Deep expertise in NetSuite or Salesforce (experience with both preferred)
• Proven success leading complex implementations
• 3+ years managing global teams
• Experience with Lead-to-Cash processes (CPQ, CLM, billing, etc.)
• Experience with integration platforms (Boomi preferred)

Technical Skills

• NetSuite: SuiteScript, SuiteFlow, ARM, multi-subsidiary
• Salesforce: Sales Cloud, CPQ, Service Cloud, Apex, LWC
• Integration: REST/SOAP APIs, iPaaS tools
• Data: Snowflake or similar, data modeling
• Project Management: Agile/Scrum, Jira, Asana

Leadership & Communication

• Strong executive communication skills
• Ability to influence cross-functional stakeholders
• Experience driving organizational change
• Thrives in fast-paced environments

Preferred Qualifications

• NetSuite or Salesforce certifications
• Boomi certification
• Experience with Snowflake
• Familiarity with SOC 2, NIS2 compliance
• Experience in post-acquisition environments

For more information please see the Benefits Highlights brochure for regular, full-time employees. 

In addition, you can access the Benefit Highlights brochure for regular, full-time employees by copying and pasting the link into your browser: https://www.platformscience.com/benefit. 

Our job titles for each posting may span across more than one job level. The estimated base salary for this role is between $120,000  and  $165,000 The range displayed on each job posting reflects the minimum and maximum target range for new hire base salaries across all US locations. Compensation packages are based on many factors unique to each candidate, including but not limited to skill set, work experience, relevant training and certifications, business needs, market demands and specific geographical location. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, and benefits.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.