The Role:

• As an Applied Value Engineer you are pushing the envelope in solving business-critical problems for our customers. You will be working with our most strategic customers, understanding their objectives and key challenges, and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

The work you’ll do:

• AI Discovery & Solutioning: Understand customers AI strategy and business critical challenges. As Celonis product & domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle
• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude and don’t shy away from complex problems. Leverage cutting edge AI technologies to rapidly build creative prototypes in customer hackathons solving business critical problems
• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale enabling a fundamental shift in business operations from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform
• Proof projects: End-to-end execution of business-critical Proof-of-Value projects, incl. architecture and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails; integrating with enterprise data, identity, and compliance frameworks.
• Ensure Successful Project Outcome: Applied AI Solution Engineer stay involved with projects until agreed value & adoption thresholds are reached
• Specialize in Domains or Industries: To scale knowledge across the organization Applied AI Solution Engineers specialize in domains (e.g. supply chain) and industries

The qualifications you need:

• 3-5 years of experience leading technical pre-sales, including defining AI roadmaps, building compelling ROI/TCO business cases and prototyping of machine learning and generative AI solutions.
• Understanding of generative AI techniques like RAG, few shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning that are used to build high-impact use cases like intelligent chatbots and automated text processors.
• Understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• Good knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies.
• Strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails.
• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex)

Smartsheet is establishing a new Enterprise Insights & Intelligence team to centralize ownership of corporate metrics, analytics governance, and self-serve data enablement. This is a foundational hire — you will help build this function from the ground up, with direct visibility to senior leadership and the opportunity to shape how the entire organisation consumes and trusts its data.

We are looking for a Senior Business Intelligence Engineer who can operate across three strategic pillars: automating and governing corporate executive reporting, standardising metrics and reporting practices at scale, and enabling self-serve and AI-powered data solutions. Day to day, this means you could be building an automated executive scorecard, codifying metric definitions into a governed semantic layer, standing up an AI agent that lets business users query trusted data in natural language, or leading enablement sessions on our analytics platforms. The thread connecting all of it is ensuring that Smartsheet's data is trusted, consistent, accessible, and ready for both human and AI consumption.

This is not a traditional reporting or data science role. You will work across dbt, MetricFlow, Snowflake, and Databricks to build the governed data layer that underpins everything — from board-level scorecards to LLM-powered insights to self-serve dashboards.

You Will

• Design, build, and maintain governed metric models — standardised, reusable definitions of business KPIs that dashboards, reports, and AI agents all query from a single source of truth
• Own the automation and maintenance of corporate scorecards and executive reporting (SLT/XLT), ensuring trusted, timely data with AI-powered anomaly detection and alerting
• Conduct deep dives on key KPIs and company goals, surfacing actionable insights and translating short- and long-term business priorities into data-driven recommendations shared via reviews and async updates
• Lead metric certification and governance — maintain a centralised KPI glossary, standardise dashboards, and retire stale reporting assets
• Build AI agent integrations (MCP servers, skills, subagents) that allow tools like Claude and Snowflake Cortex to query enterprise data through the semantic layer with metric-correct SQL
• Drive self-serve analytics enablement — documentation, training, dashboard quality checks, and experimentation governance across Amplitude, Tableau, and other platforms
• Partner with Product, Engineering, Finance, GTM, and Customer Success to align metric definitions and data sources cross-functionally
• Translate qualitative UX signals and customer feedback into measurable data pipelines

You Have

• Bachelor's degree (B.Tech / B.E. / B.Sc.) in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative field
• 5+ years of experience in analytics engineering, BI engineering, data engineering, or a closely related role
• Experience with KPI design and insight generation — ability to define meaningful metrics, analyse trends, identify anomalies, and communicate findings that drive business decisions
• Familiarity with dbt (dbt Core or dbt Cloud) and concepts like YAML-based metric definitions and reusable data models; hands-on experience is a plus but not required
• Deep SQL expertise with experience working in cloud data platforms such as Snowflake and/or Databricks
• Experience building semantic layers, governed data models, or canonical metric definitions for downstream consumption
• Working familiarity with AI/LLM tooling — concepts such as MCP (Model Context Protocol), agentic frameworks, or tool-use patterns for large language models
• Proficiency with one or more BI/visualisation tools (Tableau, Amplitude, or similar)
• Strong cross-functional collaboration skills and excellent async communication across time zones (IST / US Pacific overlap expected)
• A proactive, ownership-driven mindset — comfortable building new processes and standards in a greenfield environment

Preferred Qualifications

• Experience building AI agent skills, subagents, or MCP server integrations for LLMs
• Hands-on experience using agentic coding platforms (Claude Code, Cursor, Windsurf, etc.) to streamline and automate analytics workflows
• Software engineering experience (Python, JavaScript/TypeScript) with the ability to contribute to application-level instrumentation code
• Experience with event taxonomy design, behavioural analytics pipelines, or product instrumentation (Amplitude, Segment, etc.)
• Familiarity with metric governance frameworks, data catalogues, or data quality tooling
• Prior experience working in a SaaS or enterprise software environment

For over 20 years, Smartsheet has helped people and teams achieve–well, anything. As the Intelligent Work Management Platform, we are redefining the velocity of work by uniting people, data, and AI to move businesses forward. We don’t just automate tasks; we eliminate execution silos and turn strategic vision into measurable enterprise impact. We’re creating a space to think big and take action, because when challenge meets purpose and AI-powered execution meets human ingenuity, that’s magic at work. It’s what we show up for every day, helping organizations not just keep up with change, but thrive because of it.

Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Manager AI/ML Ops Engineering, who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.

You Will:

• Focus on team members and coaching them to play to their strengths, grow and deliver peak performance
• Lead and mentor a team of AI/ML Ops engineers and operations specialists.
• Define and govern solutions for AI/ML operations, ensuring scalability, cost-efficiency, and reliability
• Develop and maintain standardized AI/MLOps workflows, including CI/CD/CT (Continuous Integration/Continuous Delivery/Continuous Training) pipelines
• Delegate and harness the aggregate strength of your team.
• Focuses on individual and team needs to foster a positive culture consistent with Smartsheet values.
• Actively helps individuals and the overall team to set priorities and focus on delivery of commitments
• Review team's designs and provide feedback on deployment safety, resilience, scale, performance, and security
• Lead and facilitate cross-team interactions, communication, and dependencies
• Ensure all changes are fully tested before being deployed
• Ensure deployment plans are well-considered and include appropriate scalability and load tests
• Work with stakeholders to align AI projects with business strategies.
• Ensure all AI/ML Ops solutions adhere to regulatory compliance, security, and ethical guidelines
• Drive Engineering and Operational excellence initiatives
• Perform other duties as assigned
  
  

You Have:

• Enterprise SaaS software solutions with high availability and scalability
• Experience building teams through recruiting and retention
• Experience in Leading and Mentoring a team of ML engineers and operations specialists.
• Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security
• AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
• Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
• Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
• Programming languages like Python and SQL
• Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
• Solution Cost Optimisations and design to cost
• Legally eligible to work in India on an ongoing basis

Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Senior AI & Data Governance Engineers who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.

You Will:

• Develop and enforce AI&Data governance frameworks, including bias detection, explainability, and model lifecycle management
• Ensure adherence to data privacy laws and security regulations, managing risks in AI and data pipelines
• Implement data lineage, metadata, data management, and quality frameworks
• Implementing tools to track data from its source to the final AI output. If a model breaks, you need to know exactly which data point caused the drift
• Define roles for data custodians, users, and AI developers, promoting transparency and fairness.
• Partner with Legal, Data Engineering, and Security teams to embed security and privacy into AI workflows and data products
• Implement governance tools (e.g., Collibra, Informatica) and automate audit procedure
• Oversee data stewardship to ensure data accuracy, integrity, and privacy throughout its lifecycle
• Designing and enforcing the rules for how data is collected, stored, and used—specifically focusing on data privacy (GDPR, CCPA) and AI regulations (like the EU AI Act).
• AI Ethics & Bias Mitigation: Establishing "Responsible AI" standards. This involves auditing models for algorithmic bias, ensuring transparency (Explainable AI), and managing the ethical implications of automated decision-making
• Risk Management through Identification of Shadow AI (unauthorized use of AI tools) and managing the risks associated with third-party LLM providers
  
  

You Have:

• Experience in AI Governance across foundational pillars like AI Organization, Legal, Regulatory Compliance, Ethics, Transparency, Interoperability, Data/AIOps Infrastructure, AI protection and Security
• AI Risk Assessment & Management, Auditability & Transparency, AI Policy Development
• Databricks AI Governance Framework (DAGF), Databricks Security Framework (DASF), MLFlow, Unity Catalog, RAG Governance
• Programming languages like Python and SQL
• Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
• In-depth understanding of AI, GenAI, LLMs, data quality assessment, and metadata management.
• Regulatory Knowledge in GDPR, EU AI Act, and industry-specific regulations (e.g., HIPAA, Financial Services)
• Lineage Tracking with automatic capture of end-to-end data flow (from ETL to BI/AI) to understand dependencies.
• Auditability with centralized logs to allow compliance teams to monitor access and usage of data and AI models
• Knowledge of tools for Model Auditing towards Bias detection,, monitoring, and mitigating bias
• Understanding of data masking, encryption, and SOC2
• Certifications like CIPP (Privacy), CDMP (Data Management), or specialized AI ethics certifications is preferable
• Enterprise SaaS software solutions with high availability and scalability
• Legally eligible to work in India on an ongoing basis

Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Senior AI/ML Ops Engineers who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.

You Will:

• Designing, Developing and overseeing the strategy and architecture of scalable and reliable AI/ML Ops platforms / pipelines
• Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable
• CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools
• Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms
• Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable
• Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time.
• Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable
• Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users
• Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production.
• Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow.
• Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
• Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure
• Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
• Perform other duties as assigned

You Have:

• Enterprise SaaS software solutions with high availability and scalability
• Solution handling large scale structured and unstructured data from varied data sources
• Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security
• Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
• In depth experience in System design, AI/ML Frameworks and tools involving large Petabytes of data with Databricks Lakehouse ecosystem
• AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
• Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
• Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
• Programming languages like Python and SQL
• Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
• Solution Cost Optimisations and design to cost
• Legally eligible to work in India on an ongoing basis

Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Senior AI/ML Ops Engineers who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.

You Will:

• Designing, Developing and overseeing the strategy and architecture of scalable and reliable AI/ML Ops platforms / pipelines
• Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable
• CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools
• Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms
• Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable
• Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time.
• Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable
• Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users
• Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production.
• Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow.
• Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
• Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure
• Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
• Perform other duties as assigned

You Have:

• Enterprise SaaS software solutions with high availability and scalability
• Solution handling large scale structured and unstructured data from varied data sources
• Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security
• Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
• In depth experience in System design, AI/ML Frameworks and tools involving large Petabytes of data with Databricks Lakehouse ecosystem
• AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
• Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
• Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
• Programming languages like Python and SQL
• Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
• Solution Cost Optimisations and design to cost
• Legally eligible to work in India on an ongoing basis

Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Principal Data & AI/ML Ops Engineers, who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform. 

You Will:

• Data Architecture and Design: Designing and overseeing the architecture of scalable and reliable data platforms, including data pipelines, storage solutions, and processing systems
• Data Modelling and Management:Developing and implementing data models, ensuring data quality, and establishing data governance policies
• Data Pipeline Development: Building and optimising data pipelines for ingesting, processing, and transforming large datasets from various sources
• Performance Optimisation: Identifying and resolving performance bottlenecks in data pipelines and systems, ensuring efficient data retrieval and processing
• Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure
• Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
• Data Security and Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
• Perform other duties as assigned

You Have:

• Enterprise SaaS software solutions with high availability and scalability
• Solution handling large scale structured and unstructured data from varied data sources
• Experience in building and maintaining data platform systems such as distributed compute, data orchestration, distributed storage, streaming infrastructure ensuring scalability, reliability, efficiency and security
• Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
• In depth experience in System design involving large Petabytes of data with Databricks Lakehouse
• Experience in modern AI/Data infrastructure patterns, Semantics layer Organizing data for AI agents (metadata, context)
• AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
• Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
• Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
• Programming languages like Python, SQL, and potentially Java or Scala
• Exposure to Snowflake and Data pipeline frameworks like Airbyte/Airflow is preferable
• Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
• Solution Cost Optimisations and design to cost
• Driving engineering excellence initiatives
• Legally eligible to work in India on an ongoing basis

About WPP Media 

WPP is the creative transformation company. We use the power of creativity to build better futures for our people, planet, clients and communities. For more information, visit wpp.com. 

WPP Media is WPP’s global media collective. In a world where media is everywhere and in everything, we bring the best platform, people, and partners together to create limitless opportunities for growth. For more information, visit wppmedia.com 

At WPP Media, we believe in the power of our culture and our people. It’s what elevates us to deliver exceptional experiences for both our clients and each other. In this role it will be critical to embrace WPP & WPP Media’s shared core values: 

• Be Extraordinary by Leading Collectively to Inspire transformational Creativity. 
• Create an Open environment by Balancing People and Client Experiences by Cultivating Trust. 
• Lead Optimistically by Championing Growth and Development to Mobilize the Enterprise. 

Key Responsibilities: 

• Design, develop, and optimize enterprise ETL/ELT pipelines utilizing Azure Data Factory, Azure Data Lake Storage, and advanced serverless technologies—ensuring cross-platform scalability, security, and reliability. 

• Architect and implement highly efficient, complex SQL solutions—including advanced query optimization, partitioning, and indexing—to power sophisticated analytics models and enable real-time data processing. 

• Lead the development and integration of robust automation frameworks using Python, and API orchestration, introducing innovative solutions to streamline the entire data lifecycle and maximize operational efficiency. 

• Exercise full ownership of production pipeline reliability; proactively identify and resolve critical issues through deep root-cause analysis, and institute resilient, long-term stability measures for continuous uptime. 

• Establish, refine, and enforce rigorous coding and architectural standards through comprehensive code reviews and technical audits, setting quality benchmarks for the offshore engineering team. 

• Serve as a liaison with onshore leadership, driving strategic backlog prioritization, release management, and complex cross-regional project coordination to align with organizational objectives. 

• Champion best-in-class documentation, data lineage, and automated CI/CD deployment practices, ensuring transparency, auditability, and governance across all data assets. 

• Assist with enterprise capacity planning, resource optimization, and architectural design of innovative data solutions tailored to evolving business requirements. 

• Demonstrate expert-level support for analytics and media teams, translating business challenges into scalable, high-performance technical solutions, leveraging deep Azure and SQL expertise. 

Senior-Level Expectations: 

• Act as the organization’s subject matter expert (SME) in end-to-end pipeline architecture, orchestration frameworks, schema evolution, and advanced Azure Data Factory strategies. 

• Mentor and develop junior and mid-level engineers through structured coaching, technical workshops, and ongoing knowledge transfer, cultivating a high-performance engineering culture. 

• Lead modernization initiatives across the organization, championing the adoption of technologies such as Databricks, DBT and advanced DevOps practices to future-proof the data platform and enable rapid innovation. 

• Ensure strict adherence to SLAs and regulatory compliance through advanced monitoring, proactive risk mitigation, and continuous improvement of operational processes. 

Required Skills 

• 5-6years of progressive experience in data engineering, with expert-level mastery of Azure Data Factory, SQL, and cloud data platforms (Azure and/or GCP). 
• Provenexpertisein designing, optimizing, and managing large-scale, production-grade data pipelines, including deep skills in SQL performance tuning, ADF orchestration, and CI/CD automation. 
• Advanced knowledge of production operations, troubleshooting, and high-availability data processing at scale.

Good to Have 

• Adverity
• Dataflow
• Big Query
• Databricks
• DBT
• Terraform
• Wrike/Jira/Azure DevOps
• DP‑203 / GCP Data Engineer certifications

Life at WPP Media & Benefits 

Our passion for shaping the next era of media includes investing in our employees to help them do their best work, and we’re just as committed to employee growth as we are to responsible media investment. WPP Media employees can tap into the global WPP Media & WPP networks to pursue their passions, grow their networks, and learn at the cutting edge of marketing and advertising. We have a variety of employee resource groups and host frequent in-office events showcasing team wins, sharing thought leadership, and celebrating holidays and milestone events. Our benefits include competitive medical, group retirement plans, vision, and dental insurance, significant paid time off, preferential partner discounts, and employee mental health awareness days.   

WPP Media is an equal opportunity employer and considers applicants for all positions without discrimination or regard to characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.

We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process. 

#LI-GOC

About the team & role:

• The Information Security organisation advances the overall state of security at Rubrik through critical initiatives and the coordination of large security projects. Information Security builds technologies, tools, and processes to better enable teams at Rubrik to develop secure software and protect data and systems with appropriate security controls. Information Security also develops systems to monitor and respond to attacks against our systems, provides awareness education to teams on security best practices for data protection, and ensures data sharing relationships with third parties in order to securely protect Rubrik information.

• We are seeking a Senior Security Engineer to bridge the gap between traditional Security Operations and modern Data Engineering. You will be responsible for the day-to-day health of our SIEM ecosystem while simultaneously contributing in transition toward a Security Data Lake architecture. This is a hands-on, high-impact role that leverages Programming, Cloud Warehouses and AI to defend a global multi-cloud footprint.

What you’ll do?

• SIEM Administration: Handle day-to-day operations of market-leading SIEM platforms (e.g., Splunk, Sentinel, or Chronicle). This includes log ingestion from a variety of sources like Network devices, 3rd party vendor APIs,  Cloud Services, Webhooks etc..  parsing/normalisation to a common schema, health monitoring checks,  User access management and Cost Monitoring.
• Security Data Lake Operationalisation: Develop and maintain the infrastructure/Platform that moves security telemetry from raw sources into Snowflake, BigQuery, or Databricks. Tune/Optimise Ingestion at Scale for cost efficiency and  Enable SOC team and Threat Detection team to leverage the Security Data lake for their Search and Analytics workloads. 
• AI & Agentic Automation: Proactively integrate AI tools and LLMs into daily workflows; develop AI agents to automate Tier 1/2 SecOps tasks like Incident Investigation and Response.
• Cross-Team Collaboration: Partner with global teams across time zones and manage Stakeholder communication.

Experience you'll need:

• Experience: 5+ years in Security Ops and Engineering, focusing on  Security Data management and Automation.
• SIEM and SOAR Mastery: Hands-on experience with at least one market-leading SIEM (Splunk, Microsoft Sentinel, Elastic) and SOAR platform (Palo Alto XSOAR, Splunk SOAR).
• Cloud Data Warehousing: Practical experience administering or developing within Snowflake, BigQuery, and/or Databricks. Prior experience in building/maintaining data platforms that can manage  50-100 TB/day data is a big plus.
• Programming: Strong proficiency in Python and Shell scripting.
• Data Engineering Knowledge: Understanding of Cloud warehouse and  Lakehouse concepts, Open Table formats and Search engines for a composable Security Data stack.
• Cloud Infrastructure: Solid experience in one major cloud (AWS/GCP/Azure); Multi-cloud familiarity is a major plus.
• AI Fluency: Demonstrated experience or strong inclination towards utilising various AI tools to significantly enhance effectiveness (force multiplier) and solve complex business problems, particularly within SecOps and GRC domains.
• Nice to have
  • Exposure to Cloud Logging frameworks and best practices for Security Telemetry ingestion.
  • Familiarity with container orchestration (Kubernetes/EKS/GKE).
  • Interest/experience in building AI-driven security workflows.
  • Knowledge of modern CI/CD patterns and DevOps security integrations.
  • Experience with Terraform or other IaC tools.

Role Description

• As a Senior Applied Value Engineer you are pushing the envelope in solving business-critical problems for our customers. You will be working with our most strategic customers, understanding their objectives and key challenges, and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

Key Responsibilities:

• AI Discovery & Solutioning: Understand customers AI strategy and business critical challenges. As Celonis product & domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle
• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude and don’t shy away from complex problems. Leverage cutting edge AI technologies to rapidly build creative prototypes in customer hackathons solving business critical problems
• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale enabling a fundamental shift in business operations from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform
• Proof projects: End-to-end execution of business-critical Proof-of-Value projects, incl. architecture and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails; integrating with enterprise data, identity, and compliance frameworks.
• Ensure Successful Project Outcome: Senior Applied Value Engineer stay involved with projects until agreed value & adoption thresholds are reached
• Specialize in Domains or Industries: To scale knowledge across the organization Senior Applied Value Engineer specialize in domains (e.g. supply chain) and industries

Requirements:

• 6+ years of experience leading technical pre-sales, including defining AI roadmaps, building compelling ROI/TCO business cases and prototyping of machine learning and generative AI solutions.
• Understanding of generative AI techniques like RAG, few shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning that are used to build high-impact use cases like intelligent chatbots and automated text processors.
• Understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• Good knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies.
• Strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails.
• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex)

Role Description

• As a Senior Applied Value Engineer you are pushing the envelope in solving business-critical problems for our customers. You will be working with our most strategic customers, understanding their objectives and key challenges, and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

Key Responsibilities:

• AI Discovery & Solutioning: Understand customers AI strategy and business critical challenges. As Celonis product & domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle
• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude and don’t shy away from complex problems. Leverage cutting edge AI technologies to rapidly build creative prototypes in customer hackathons solving business critical problems
• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale enabling a fundamental shift in business operations from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform
• Proof projects: End-to-end execution of business-critical Proof-of-Value projects, incl. architecture and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails; integrating with enterprise data, identity, and compliance frameworks.
• Ensure Successful Project Outcome: Senior Applied Value Engineers stay involved with projects until agreed value & adoption thresholds are reached
• Specialize in Domains or Industries: To scale knowledge across the organization Applied AI Engineers specialize in domains (e.g. supply chain) and industries

Requirements:

• 6+ years of experience leading technical pre-sales, including defining AI roadmaps, building compelling ROI/TCO business cases and prototyping of machine learning and generative AI solutions.
• Understanding of generative AI techniques like RAG, few shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning that are used to build high-impact use cases like intelligent chatbots and automated text processors.
• Understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• Good knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies.
• Strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails.
• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex)

**This is a hybrid position that requires 2 days per week in office at our Bangalore location**

Reporting to Sr Director, The PMO Analyst will be working closely with project/team leads across multiple functions and regions, the PMO Analyst will administer core PMO tools, maintain key reports and dashboards, and help ensure that project and portfolio information is accurate, timely and accessible. This role suits someone detail oriented who enjoys working with data, has excellent knowledge and experience of PMO tools/systems and is ready to embrace AI and automation within PMO.

HOW WE’LL BE WINNING TOGETHER DAY TO DAY

• Administer and support core PMO tools, including PSA and related platforms/integrations (e.g. SuiteProjects Pro/OpenAir, Wrike, Salesforce, ADP) in line with agreed standards.
•  Build, maintain and improve operational and portfolio reports and dashboards using BI and associated tools (e.g. Power BI, Databricks, Excel, AI & automation tools).
•  Produce regular project and portfolio reporting for PMO, Ops and global leadership teams, ensuring data is accurate, consistent and clearly presented.
•  Support tracking of portfolio health, risks, issues, utilization and capacity, highlighting trends or anomalies for further review.
•  Monitor and govern adherence to agreed PMO processes and templates, and work with PMs and functional teams to resolve basic process or data issues.
•  Contribute to continuous improvement by suggesting enhancements to tools, reports and processes, including opportunities for automation and AI-assisted efficiency.
•  Act as a helpful point of contact for PMO tooling and reporting queries, working effectively across time zones.
•  Contribute to building a modern, AI-enabled PMO capability.
• Act as the go-to expert for PMO tooling, supporting users and resolving data/process issues.
• Go beyond reporting: highlight trends, risks, and actionable insights (capacity issues, utilization trends, delivery risks).

   WE SHOULD TALK IF THIS SOUNDS LIKE YOU

• Bachelor’s degree in business, Information Systems, Engineering, Mathematics or a related field.
• 3–7 years’ experience in PMO, reporting, business analysis, operations or similar data/analytics-oriented roles.
• Experience in a professional services, SaaS or technology implementation environment is advantageous.
• Strong Excel skills (formulas, pivot tables, lookups, basic modelling).
• Practical experience with BI/reporting tools (e.g. Power BI, Tableau or similar).
• Experience with PSA or PPM tools and a good understanding of project, resource and time-entry data (e.g. SuiteProjects Pro, Wrike etc).
• Familiarity with CRM tools (e.g. Salesforce) is an advantage.
• Strong knowledge of and interest in AI tools, automation trends & innovations (particularly Copilot)
• Experience working in or alongside a PMO, project support, reporting or business operations function.
• You will own the integrity, usability, and evolution of PMO data, reporting, and tooling, ensuring leadership has accurate, timely, and actionable insights.
• Understanding basic project management concepts such as agile, waterfall, full project lifecycle, RAID, status reporting, change control etc.
• Able to work across multiple projects simultaneously and pivot to new initiatives at short notice as required.
• High attention to detail and strong focus on data accuracy and completeness.
• Excellent written and verbal communication skills (English)
• Ability to work independently, manage multiple tasks, and meet deadlines in a global, remote setting.
• Proactive mindset: identifies problems and drives solutions, not just reports them.
• Confident working with stakeholders across functions and seniority levels.

The Role:

As an Applied Value Engineer for the Japan Market, you will solve business-critical problems for our most strategic Japanese customers. You will bridge the gap between cutting-edge AI technology and the unique business requirements of Japanese enterprises.
Working with the world’s leading Process Intelligence (PI) platform and partners like Microsoft, OpenAI, and Databricks, you will feed operational context to AI to help Japanese organizations industrialize AI and unlock real ROI. You will prototype solutions, demonstrate value to executives, and ensure successful implementation and adoption within the Japanese business ecosystem

The work you’ll do:

• AI Discovery & Solutioning (Japan Focus): Understand the specific AI strategies and challenges of Japanese customers. Translate their requirements into innovative solutions that align with local business practices.
• Hackathons & Prototyping: Rapidly build creative prototypes (LLM/Agent-based) to solve business-critical problems during customer hackathons.
• Agentic Process Transformation: Enable a fundamental shift for our customers from traditional automation to autonomous AI agents empowered by the Celonis PI Platform.
• Proof Projects: Execute end-to-end Proof-of-Value (PoV) projects, including architecture, RAG, and guardrails, ensuring compliance with enterprise data and identity frameworks.
• Cross-Border Collaboration: Work closely with the Japan-based account teams and executives to ensure project outcomes reach agreed value and adoption thresholds.
• Domain Specialization: Specialize in domains (e.g., Supply Chain, Finance) to scale knowledge across the Japan and global organizations.

The qualifications you need:

• Market Alignment: Strong willingness and commitment to work specifically for the Japan market. This includes flexibility to align with Japan Standard Time (JST) for key meetings and workshops.
• Professional Experience: 3-5 years of experience in technical pre-sales, defining AI roadmaps, and building ROI/TCO business cases.
• Technical Expertise: Deep understanding of Generative AI techniques (RAG, multi-agent orchestration, prompt engineering) and Python (LangChain, pandas, PyTorch, etc.).
• Process Knowledge: Understanding of business processes (Supply Chain, Finance, etc.) and the ability to translate high-level needs into AI use cases.
• Communication: Strong presentation skills to engage with both internal stakeholders and external Japanese enterprise executives.
• Education: Bachelor’s Degree required (Master’s in CS, Engineering, or Math preferred).

• Japan Market Experience: Previous experience working with Japanese companies as clients or partners is highly valued.
• Cultural Competency: Familiarity with Japanese business etiquette and communication styles.
• Hands-on AI implementation: Experience building agentic systems and deploying models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex).
• LLM Ecosystem: Working knowledge of LangChain, LlamaIndex, or other OSS packages.

Product Management at InMobi: We offer an opportunity to have immediate impact with the company and our products. You shall be working at the cutting edge of technology connecting various businesses at InMobi centrally. The work that you shall do will be mission critical for InMobi and is in direct path for success of multiple of core product offerings in InMobi.

Our Product leaders at InMobi own the business strategy behind the product by building subject matter expertise, define its functional requirements aligned to various user personas through PRDs, and drive the launch of product features by owing the management of its development cycle with peer Engineering teams.  We design world-class products within one of the fastest growing companies in this space with a truly global footprint. 

Role: Senior Product Manager – Data & AI Platform for the Central Data Repository & AI Platform Team

As a Senior Product Manager – Data & AI, you will be responsible for driving the roadmap for InMobi’s next-generation data and AI infrastructure — unifying data across products, systems, and business functions while enabling the company to leverage artificial intelligence responsibly and effectively.

You will work across cross-functional teams — including Engineering, Data Science, Analytics, and Business Operations — to deliver scalable platform capabilities that power automation, predictive insights, and operational excellence.

What You’ll Do

1. Product Strategy & Vision

• Define and evolve the product vision and roadmap for InMobi’s enterprise Data & AI Platform — including CDR, Unified Data Warehouse (UDW), and AI/ML enablement capabilities.
• Align platform goals with InMobi’s strategic business and data transformation objectives.
• Identify opportunities to integrate AI across business systems to improve process efficiency, accuracy, and decision intelligence.

2. Platform Ownership

• Own the product lifecycle for core data platform components — from data ingestion and transformation to data governance, modeling, and AI pipeline integration.
• Collaborate with engineering teams to design and deliver scalable, secure, and efficient data and AI systems leveraging technologies such as Databricks, Power BI, and cloud-native data platforms.
• Build foundational capabilities that enable AI experimentation, model deployment, and monitoring at scale.

3. Execution Excellence

• Translate complex business requirements into detailed PRDs, user journeys, and data product specifications.
• Partner closely with data engineering and AI teams to define sprint goals, manage backlogs, and ensure timely delivery.
• Be hands-on with platform interfaces and datasets to validate requirements and drive insights during BAU and transformation cycles.

4. Cross-Functional Collaboration

• Work closely with finance, sales, account management, and product stakeholders to design integrated data and AI solutions that serve cross-enterprise use cases.
• Drive alignment across global teams — product, engineering, data science, and business — ensuring all dependencies are managed effectively.
• Be the single Product POC for Engineering counterparts to define platform logic, edge cases, and implementation details.

5. AI & Analytics Integration

• Partner with AI scientists and ML engineers to prioritize and productize AI use cases that drive measurable business impact.
• Define frameworks for responsible AI adoption, ensuring transparency, explainability, and compliance across systems.
• Enable a self-serve analytics and AI ecosystem for users across InMobi.

What We Expect from You

• Experience: 9+ years overall with 7+ years in Product Management, building and scaling enterprise-level data and AI products.
• Domain Expertise: Strong understanding of data warehousing, data governance, analytics platforms, and AI/ML systems.
• Technical Acumen: Ability to work with large datasets, define data models, and collaborate with engineering teams on architecture and integrations.
• Analytical Mindset: Deep comfort with data-driven decision-making; familiarity with SQL, BI tools, and data pipelines.
• AI Product Fluency: Knowledge of ML lifecycle management, model training/deployment workflows, and AI platform integration.
• Leadership: Experience guiding junior PMs, leading cross-functional planning, and managing competing priorities with clarity.
• Collaboration: Strong stakeholder management skills, with the ability to drive consensus across global, multi-functional teams.
• Execution Bias: A self-starter who thrives in ambiguity, connects dots across domains, and delivers outcomes that move the needle.

Preferred Experience

• Experience in enterprise system transformation programs involving CRM, ERP, and monetization platforms.
• Familiarity with data privacy, security, and ethical AI frameworks.
• Prior experience in digital marketing, ad-tech, or data-driven B2B platforms.

Why Join InMobi

• Drive InMobi’s enterprise-wide data and AI transformation and shape the future of how intelligence powers our products and decisions.
• Collaborate with world-class teams across engineering, AI, and business to deliver high-impact solutions.
• Work in a culture that values ownership, innovation, and continuous learning.
• Be part of an organization consistently recognized as a Great Place to Work and one of the World’s Most Innovative Companies.

Industry

• Marketing & Advertising
• Data & AI Platforms
• Enterprise Software

Job Function

• Product Management – Data & AI Platform
• Enterprise Transformation & Systems Integration

Role Description

• As an Applied Value Engineer you are pushing the envelope in solving business-critical problems for our customers. You will be working with our most strategic customers, understanding their objectives and key challenges, and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

Key Responsibilities:

• AI Discovery & Solutioning: Understand customers AI strategy and business critical challenges. As Celonis product & domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle
• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude and don’t shy away from complex problems. Leverage cutting edge AI technologies to rapidly build creative prototypes in customer hackathons solving business critical problems
• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale enabling a fundamental shift in business operations from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform
• Proof projects: End-to-end execution of business-critical Proof-of-Value projects, incl. architecture and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails; integrating with enterprise data, identity, and compliance frameworks.
• Ensure Successful Project Outcome: Applied AI Engineers stay involved with projects until agreed value & adoption thresholds are reached
• Specialize in Domains or Industries: To scale knowledge across the organization Applied AI Engineers specialize in domains (e.g. supply chain) and industries

Requirements:

• 5+ years of experience leading technical pre-sales, including defining AI roadmaps, building compelling ROI/TCO business cases and prototyping of machine learning and generative AI solutions.
• Experience in Oil & Gas industry is must.
• Understanding of generative AI techniques like RAG, few shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning that are used to build high-impact use cases like intelligent chatbots and automated text processors.
• Understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• Good knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies.
• Strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails.
• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex)

At Reltio®, we believe data should fuel business success. Reltio’s AI-powered data unification and management capabilities—encompassing entity resolution, multi-domain master data management (MDM), and data products—transform siloed data from disparate sources into unified, trusted, and interoperable data. Reltio Data Cloud™ delivers interoperable data where and when it's needed, empowering data and analytics leaders with unparalleled business responsiveness. Leading enterprise brands—across multiple industries around the globe—rely on our award-winning data unification and cloud-native MDM capabilities to improve efficiency, manage risk and drive growth.

At Reltio, our values guide everything we do. With an unyielding commitment to prioritizing our “Customer First”, we strive to ensure their success. We embrace our differences and are “Better Together” as One Reltio. We are always looking to “Simplify and Share” our knowledge when we collaborate to remove obstacles for each other. We hold ourselves accountable for our actions and outcomes and strive for excellence. We “Own It”. Every day, we innovate and evolve, so that today is “Always Better Than Yesterday”. If you share and embody these values, we invite you to join our team at Reltio and contribute to our mission of excellence.

Reltio has earned numerous awards and top rankings for our technology, our culture and our people. Reltio was founded on a distributed workforce and offers flexible work arrangements to help our people manage their personal and professional lives. If you’re ready to work on unrivaled technology where your desire to be part of a collaborative team is met with a laser-focused mission to enable digital transformation with connected data, let’s talk!

Job Summary:

As a Staff Full-Stack Engineer at Reltio, you will be a key member of our new Data Quality team, responsible for building a cutting-edge Data Observability platform from scratch. This platform will provide automated profiling and anomaly detection across various data sources, including Cloud Data Warehouses (Snowflake, BigQuery, Databricks, Redshift), dbt, Kafka/streaming, and SaaS applications (SFDC/Dynamics). You will contribute to both the API and UI development, ensuring a robust and intuitive experience. This is an individual contributor role.

Job Duties and Responsibilities:
(IC: Knowledge | Leadership | Communication)
(MGR: Knowledge | People Management & Leadership | Strategic Impact)
● Design, develop, and maintain the Data Observability platform using Python for the agentic and backend services.
● Implement robust and scalable APIs for seamless integration with various data sources
● Collaborate with frontend engineers on UI design and contribute to UI development as needed.
● Collaborate with cross-functional teams to define requirements, design solutions, and ensure the successful delivery of the platform.
● Contribute to the entire software development lifecycle, from conceptualization and design to deployment and ongoing maintenance
● Ensure the platform's performance, reliability, and security through rigorous testing and adherence to best practices
● Mentor junior/middle engineers and contribute to a culture of technical excellence and continuous improvement.

Skills You Must Have:
● 7+ years of experience in enterprise software development, building scalable backend platforms.
● Expert hands‑on experience developing backend services and platform APIs using Python (e.g., FastAPI, Flask, Django).
● Proven track record of delivering high‑quality enterprise SaaS platforms in high‑stakes environments.
● Experience delivering SaaS applications that scale and perform with low latency and high throughput.
● Strong written and verbal communication skills. Proven track record of unit and integration testing with CI/CD as part of your development process.
● Experience working with AI and automation tools to improve productivity and delivery speed (GitHub Copilot, Claude Code, Cursor, VSCode Kilo Code, etc.)

Skills That Are Nice to Have:
● Familiarity with cloud-based development using AWS, Google Cloud Platform (GCP), and/or Microsoft Azure services (such as Lambda, S3, Pub/Sub, Dataflow, or Azure Functions)
● Ability to deliver modern, intuitive UI/UX using React.js (and optionally TypeScript) with minimal guidance.
● Background in Data Quality systems, frameworks, or tools (e.g., profiling, validation, monitoring)
● Experience or understanding of Master Data Management (MDM) concepts, data modeling, and enterprise data integration patterns
● Exposure to containerization and orchestration technologies (Docker, Kubernetes)
● Familiarity with monitoring and observability stacks (Mezmo, Grafana, etc.)

Opportunity

Get Well is seeking an experienced and highly motivated Staff Data Software Engineer to help build and optimize our cloud-native data platform that powers AI, analytics, and clinical applications. You will play a key role in developing scalable, compliant data infrastructure and pipelines designed specifically for the healthcare domain, while mentoring junior engineers and leading cross-functional initiatives to drive innovation.

This is a hands-on engineering role suitable for someone who thrives at the intersection of modern data engineering, cloud-native platforms, DevOps, healthcare data, and AI enablement.  Candidates must have hands-on software development experience with at least one healthcare company—preferably in the provider space—with exposure to EHRs and core healthcare data domains.

Responsibilities

Data Engineering & Platform Development

• Design, build, and maintain scalable data pipelines supporting batch and real-time use cases.
• Develop and maintain production-grade data workflows that move and transform sensitive healthcare data across distributed systems at scale.
• Work with Spark, Databricks, Airflow/Temporal, and dbt to ingest, process, and manage structured and unstructured data.
• Design and implement reusable, efficient data models for analytics and AI/ML use cases.
• Ensure platform resiliency using CI/CD pipelines, observability tools, and logging frameworks.
• Leverage Infrastructure as Code practices using Terraform, CloudFormation, or equivalent to manage cloud resources.

Healthcare Data Integration & Compliance

• Ingest and normalize complex healthcare data sets (FHIR, HL7, CCDA, Claims, EDI, Epic/Clarity, etc.).
• Familiarity with clinical coding systems and ontologies, such as ICD-10, SNOMED CT, LOINC, or RxNorm.
• Collaborate with compliance and security teams to ensure adherence to HIPAA, GDPR, and internal controls.
• Implement fine-grained access control, encryption at rest and in transit, audit logging, and data lineage strategies.

AI & GenAI Enablement

• Work alongside AI/ML and data science teams to build pipelines feeding predictive and generative models.
• Tune data infrastructure for performance across distributed systems and hybrid data stores like SQL, MongoDB, ClickHouse.
• Prioritize scalability and flexibility in designing LLM-compatible pipelines and use GenAI best practices for healthcare use cases.
• Utilize Spark clusters and query frameworks such as SparkSQL and SPARQL for large-scale data access.
• Utilize and manage graph databases (e.g., Neo4j, Amazon Neptune, or similar) to support complex relationship modeling and healthcare data connectivity use cases.
• Enable high-quality training data pipelines and implement feature stores and model serving systems.

Data Governance, Quality & Monitoring

• Implement data quality frameworks and establish robust validation processes using tools such as Great Expectations or equivalent.
• Build automated anomaly detection tools for data drift and integrity checks.
• Support data cataloging, metadata management, and ensure consistent documentation across datasets.

Collaboration, Mentorship & Leadership

• Act as a mentor to junior engineers through code reviews, paired programming, and technical guidance.
• Lead cross-functional projects with teams including clinical informatics, architecture, security, product, and design.
• Contribute to and enforce data engineering best practices, patterns, and platform standardization.

Learning and Innovation

• Research and evaluate emerging tools and frameworks (e.g., Apache Iceberg, Delta Lake) for incorporation into the platform.
• Proactively identify opportunities to improve architecture and leverage evolving trends in GenAI and cloud-native computing.

Qualifications

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 8–12 years of experience in software or data engineering roles including at least 3 years working with large-scale or cloud-native data systems.
• Must have prior software development experience in the healthcare domain—including payers, providers, health tech, medical devices, or life sciences.
• Functional knowledge and direct experience with healthcare data types (FHIR, HL7, Claims, EDI, Epic/Clarity, etc.).
• Demonstrated experience in designing, implementing, and maintaining data pipelines that move and transform healthcare data with production-level quality, reliability, and performance.

Technical Skills

• Advanced programming experience in Python, SQL, and distributed processing with Apache Spark.
• Cloud-native platform experience with Azure.
• Proven capability with Infrastructure as Code (Terraform, CloudFormation) strongly preferred.
• Experience with data warehouses and lakes including Snowflake, Databricks, and ClickHouse.
• Familiarity working with GenAI tools and ML pipelines in production environments.
• Strong skills in data modeling, job orchestration (Airflow), data transformation (dbt), and pipeline optimization.
• Experience with DevOps/tooling stacks for CI/CD, containerization, observability, and cost optimization.
• Familiarity with data validation and anomaly detection tools such as Great Expectations.
• Experience with SparkSQL and SPARQL is a plus.

Professional Attributes

• Excellent communication and collaboration skills across cross-functional, domain, and technical stakeholders.
• Ability to lead initiatives and drive data engineering standards.
• Self-driven, with a commitment to delivering high-quality solutions in regulated and sensitive environments.

About GW RhythmX

GW RhythmX is revolutionizing healthcare through connected, AI-native intelligence that unites clinical insight, patient engagement, and system-wide care orchestration. The company combines market-leading AI precision care technology with extensive trusted patient engagement leadership to help health systems deliver the right care, at the right time, through the right clinician and channel. Its solutions are deployed across more than 150 health systems, touching more than 85M patients including 8M U.S. military veterans. The company's award-winning solutions were recognized again in 2024 by KLAS Research, Fierce Healthcare, and AVIA Marketplace. A SymphonyAI Group company, GW RhythmX leverages various firm assets, including $1B+ in R&D investment, longitudinal data related to 300 million patients, 4.4 billion total annual claims, and 1.8 million healthcare professionals at more than 3,000 facilities globally.

GW RhythmX  is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.

At ZoomInfo we encourage creativity, value innovation, demand teamwork, expect accountability and cherish results. If you are collaborative, take initiative, and get stuff done we want to talk to you! We have high aspirations for the company and are looking for the right people to help fulfil the dream. We strive to continually improve every aspect of the company and use cutting-edge technologies and processes to delight our customers and rapidly increase revenue. 

Role Overview: ZoomInfo is seeking a Data Analyst III to join the Data Operations and Analysis team. This role partners closely with Product, Engineering, and Research teams to enhance data infrastructure, improve data quality, and deliver actionable insights that drive business impact.

Key Responsibilities:

• Develop a deep understanding of data systems, pipelines, and infrastructure.
• Analyze current data processes, identify gaps, and recommend scalable improvements.
• Drive initiatives to enhance data accuracy, coverage, and efficiency.
• Collaborate cross-functionally with Data Engineering, Product, and Research teams.
• Perform advanced data analysis and present insights in a clear, structured manner.
• Mentor junior analysts and contribute to team capability building.
• Work independently to explore data, propose solutions, and execute projects end-to-end.

Core Competencies:

• Strong analytical thinking and problem-solving ability.
• Ability to work in ambiguous environments and drive clarity.
• Effective communication with both technical and non-technical stakeholders.
• High attention to detail and strong organizational skills.
• Self-driven with the ability to manage multiple priorities.

Required Qualifications:

• 5+ years of experience in analytics, data operations, or quantitative research.
• Advanced proficiency in SQL, Python, BigQuery, and Excel.
• Strong understanding of ETL processes and data quality challenges.
• Experience working with large-scale datasets.
• Familiarity with AI/ML concepts including NLP and data modeling.

Preferred Qualifications:

• Experience building or deploying AI/ML solutions.
• Exposure to tools like Tableau or Looker Studio.
• Experience with Databricks, AWS, or Airflow.
• Background in product-driven or project-based environments.

Impact: This role plays a critical part in shaping the future of ZoomInfo’s data ecosystem by improving data reliability, scalability, and strategic value.

#LI-SG2

#LI-Hybrid

Job Description – Data Engineer

About the Role

We are looking for a  candidate who is  passionate about building scalable data pipelines, optimizing data workflows, and ensuring high data quality across systems. Candidates should demonstrate strong technical foundations, the ability to work independently, and a willingness to collaborate in a dynamic environment.

Core Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines to support business and analytical needs.
• Work extensively with Databricks, Python, and PySpark to process large datasets.
• Build and manage DAGs using Apache Airflow for workflow orchestration.
• Collaborate with cross-functional teams to understand data requirements and translate them into efficient engineering solutions.
• Develop and optimize complex SQL queries and participate in data modeling activities for relational and cloud data warehouses.
• Work with Amazon S3 for data storage, ingestion, partitioning, and integration within broader data lake and pipeline ecosystems.
• Ensure high standards of data quality, reliability, and performance across all data processes.
• Contribute to documentation, best practices, and continuous improvement initiatives.

Core Technical Requirements

1. Python Programming

• Strong experience writing clean, efficient Python code for data manipulation, automation, scripting, and ETL workflows.
• Familiarity with widely used data libraries (e.g., pandas, numpy).

1. Databricks

• Hands-on experience with Databricks for distributed data processing.
• Proficiency in PySpark, Delta Lake, notebooks, and building scalable pipelines.

1. Orchestration Tools

• Apache Airflow (Required): Ability to design, implement, and maintain complex DAGs for scheduling and orchestrating workflows.
• Argo Workflows (Preferred): Experience with Kubernetes-native orchestration platforms is an added advantage.

1. SQL Skills

• Advanced SQL expertise including writing complex queries, query optimization, and working with relational/cloud data warehouses.
• Experience in data modeling and performance tuning.

1. Cloud Storage (Amazon S3)

• Practical knowledge of S3 for ingestion, storage, data partitioning, access control, and integration as part of data lake architectures.

Experience Level

 2–5 years in Data Engineering or related roles..

Preferred Personal Attributes

• Strong analytical and problem-solving skills.
• Excellent communication and collaboration abilities.
• Ability to work in a fast-paced, evolving environment.

Designation  :DevOps Engineer
Location: Bangalore
Work Mode: Hybrid
Experience Required: 2–4 years

Job Summary

We are looking for a Professional Services OPS Engineer to support client-facing data
operations and workflow execution. This role focuses on job monitoring, issue resolution,
data sharing, and operational support across multiple platforms to ensure reliable and
timely client deliverables.

Key Responsibilities

• Monitor and troubleshoot job failures in Visual Cron, Argo, and Databricks
• Perform root-cause analysis and implement fixes to maintain workflow stability
• Build, schedule, and maintain workflows using Visual Cron, Argo, Databricks Jobs, and
Snowflake Tasks
• Manage data sharing and deliveries via Databricks Share, Snowflake Share, S3, and SFTP
• Push MDE and non-MDE data to client environments post job success
• Support monthly refresh cycles, reruns, backfills, and ad-hoc operational requests
• Handle client and internal PS inquiries related to deliverables and missing files
• Collaborate with internal teams to improve operational processes

Required Skills

• Hands-on experience with job schedulers (Visual Cron preferred)
• Argo or Airflow workflow orchestration
• Strong working knowledge of Databricks
• SQL for data validation and troubleshooting
• Python for scripting and automation
• Basic knowledge of S3
• Experience with SFTP-based data deliveries

Good to Have

• Snowflake Tasks and Snowflake Share
• Azure Blob Storage Exposure and Experience supporting client-facing or production systems.

What you will do

• Architect & Scale: Design and maintain high-throughput detection systems and backend services, ensuring low latency and high reliability.
• Data Orchestration: Lead the development of robust data pipelines using Spark and Airflow to supply detection teams with high-fidelity data for ML model training and evaluation.
• Technical Leadership: Partner with Engineering Managers to define technical roadmaps, mentor junior/mid-level engineers, and drive best practices in code quality and system design.
• AI-Driven Innovation: Lead the team in adopting AI productivity initiatives, leveraging tools like Claude, OpenAI, and GitHub Copilot to accelerate the development lifecycle and automate internal workflows.
• Cross-functional Collaboration: Work closely with TPMs, Product Managers, Data Scientists, and Security Researchers to translate complex business needs into scalable technical solutions.
• Operational Excellence: Manage and optimize cloud-native infrastructure on AWS/EKS, ensuring systems are cost-effective, secure, and performant.

Must Haves

• 8+ years of professional experience: Proven track record in production-level backend development with Python or Golang.
• Data Engineering Expertise: Expert-level proficiency in building and optimizing distributed data pipelines using Spark and Airflow (or equivalent orchestration tools).
• Cloud & Infrastructure: Extensive experience managing and scaling cloud-native applications on AWS (highly preferred), GCP, or Azure, with a proven track record of hands-on container orchestration using EKS.
• Leadership & Mentorship: Experience leading technical projects, mentoring engineers, and contributing to the long-term technical strategy of a team.
• System Design: Strong ability to design complex integrations and handle significant throughput/latency challenges.
• Problem Solving: A methodical approach to performance debugging, benchmarking, and resolving bottlenecks in large-scale systems.
• Database Proficiency: Strong experience with Postgres or similar relational databases at scale.
• Education: BS in Computer Science, Applied Sciences, or a related engineering field.

Nice to Haves

• Frontend Literacy: Familiarity with React and TypeScript to assist with internal tool visualizations.
• Data Ecosystems: Experience with Databricks, Snowflake, or similar data lakehouse architectures.
• Cybersecurity Domain: Background in threat detection, network security, or fraud prevention.
• Advanced Degrees: MS in Computer Science or Electrical Engineering.

#LI-AB2

• Innovate beyond our existing products and bring new ideas to life for Celonis.
• Ensure high quality and continuously improve procedures and practices.
• Work closely with your fellow engineers, project managers, and designers to create cohesive and efficient solutions.
• Collaborate with adjacent teams to drive a holistic project success spread across multiple geographies
• Learn and grow, not only in technical expertise but also in any other necessary aspects of making our projects reality.
• Brainstorm with the entire Celonis Labs team, research potential solutions, and ultimately bring them to life.

• Bachelor's or master's degree in a technical field (e.g., Computer Science, Software Engineering) or equivalent experience.
• 5+ years of experience as Backend Engineer with strong expertise in building microservices based products using Java, Spring framework, JPA, Hibernate is a must.
• Experience with building data pipelines in Databricks, ETL, Apache spark is a big plus.
• Relational databases; PostgreSQL a plus.
• Proficient in building cloud-native distributed systems.
• Able to demonstrate a generalist skill set across multiple technical areas besides the Backend, DevOps, Cloud Infrastructure.
• Ability to analyse and design complex software.
• Experience building scalable, fault-tolerant distributed systems.
• Proven background in building cloud-native software in the Kubernetes ecosystem, as well as with and on Hyperscalers such as AWS.
• Deep understanding of modern engineering practices (Git strategy, CI/CD, testing, …) and how to apply these to enable a team of multiple engineers.
• Problem-first attitude: you’re able to understand the needs of our customers and see technology as a means to an end, not an end in itself.
• Ability to quickly learn new things without tight supervision.
• Problem-solving attitude.
• Collaborative team spirit.

What You Will Do and Learn

As a Snowflake Architect/ Manager in Data Solutions, you’ll be responsible for designing, implementing, and testing proposed modern analytic solutions.  Working closely with our client partners and architects, you’ll develop relationships with key technical resources while delivering tangible business outcomes. 

• Manage the Data engineering lifecycle including research, proof of concepts, architecture, design, development, test, deployment, and maintenance
• Collaborate with team members to design and implement technology that aligns with client business objectives
• Build proof of concepts for a modern analytics stack supporting a variety of Cloud-based Business Systems for potential clients
• Team management experience and ability to manage, mentor and develop talent of assigned junior resources
• Create actionable recommendations based on identified platform, structural and/or logic problems
• Communicate and demonstrate a clear understanding of client business needs, goals, and objectives
• Collaborate with other architects on solution designs and recommendations.

Qualifications:

• 8+ years’ experience developing industry leading business intelligence and analytic solutions
• Must have thorough knowledge of data warehouse concepts and dimensional modelling
• Must have experience in writing advanced SQL
• Must have at least 5+ years of hands-on experience on DBT (Data Build Tool). Mandatory to have most recent hands-on experience on DBT.
• Must have experience working with DBT on one or more of the modern databases like Snowflake / Amazon Redshift / BigQuery / Databricks / etc.
• Hands-on experience with Snowflake would carry higher weightage
• Snowflake SnowPro Core certification would carry higher weightage
• Experience working in AWS, Azure, GCP or similar cloud data platform would be an added advantage
• Hands-on experience on Azure would carry higher weightage
• Must have experience in setting up DBT projects
• Must have experience in understanding / creating / modifying & optimizing YML files within DBT
• Must have experience in implementing and managing data models using DBT, ensuring efficient and scalable data transformations
• Must have experience with various materialization techniques within DBT
• Must have experience in writing & executing DBT Test cases
• Must have experience in setting up DBT environments
• Must have experience in setting up DBT Jobs
• Must have experience with writing DBT Jinja and Macros
• Must have experience in creating DBT Snapshots
• Must have experience in creating & managing incremental models using DBT
• Must have experience with DBT Docs
• Should have a good understanding of DBT Seeds
• Must have experience with DBT Deployment
• Must Experience with architecting data pipelines using DBT, utilizing advanced DBT features
• Proficiency in version control systems and CI/CD
• Must have hands-on experience configuring DBT with one or more version control systems like Azure DevOps / Github / Gitlab / etc.
• Must have experience in PR approval workflow
• Participate in code reviews and best practices for SQL and DBT development
• Experience working with visualization tools such as Tableau, PowerBI, Looker and other similar analytic tools would be an added advantage
• 2+ years of Business Data Analyst experience
• 2+ years of experience writing Business requirements, Use cases and/or user stories, for data warehouse or data mart initiatives.
• Understanding and experience on ETL/ELT is an added advantage
• 2+ years of consulting experience working on project-based delivery using Software Development Life Cycle (SDLC)
• 2+ years of years of experience with relational databases (Postgres, MySQL, SQL Server, Oracle, Teradata etc.)
• 2+ years of experience creating functional test cases and supporting user acceptance testing
• 2+ years of experience in Agile/Kanban/DevOps Delivery
• Outstanding analytical, communication, and interpersonal skillsAbility to manage projects and teams against planned work
• Responsible for managing the day-to-day client relationship on projects

The Team:

As part of the Product Management organization, we develop the platform that drives the next generation of enterprise intelligence and process improvement. We are a team of product enthusiasts who like to push the boundaries of the status quo and drive the product forward with innovative thinking.

Data Integration is the bedrock of our platform; it feeds the Process Intelligence Graph by extracting, ingesting, and managing customers' critical business data at scale. As we expand our global footprint, our new Engineering Hub in Bangalore is becoming a primary center of excellence for our data extraction capabilities. In this role, you will be a senior leader within the India hub, partnering with global product leadership to shape the strategic vision of our data pipeline and extractor ecosystem.

The Role:

We are seeking a Senior Product Manager with deep technical DNA to lead the development and scaling of our Extractor portfolio. You will own the end-to-end lifecycle for our most critical data gateways, ranging from native SAP (ECC & S/4HANA) integrations and Database (JDBC) connectors to our low-code Extractor Builder for Cloud SaaS.

As a Senior PM, you define and execute the roadmap. You will be responsible for identifying market shifts, navigating complex ERP architectures, and ensuring our data extraction remains high-performance, secure, and resilient. You will work at the intersection of engineering excellence and customer value, transforming technical complexity into seamless "plug-and-play" experiences for the world’s largest enterprises.

The work you’ll do:

• Strategic Roadmap Ownership: Lead the long-term vision for Celonis Extractors, prioritizing the expansion of our connector library across SAP, Oracle, Salesforce, and beyond.
• Platform Innovation: Drive the evolution of the Extractor Builder, enabling customers to build custom REST API connectors with an AI-first approach.
• Scale & Performance: Partner with engineering to optimize delta-load logic and real-time streaming capabilities to handle massive enterprise datasets.
• Cross-Functional Leadership: Act as a bridge between the local engineering teams and global stakeholders (Product, Sales, and Global Alliances) to ensure local execution aligns with global strategy.
• Customer Advocacy & Mentorship: Deep-dive into complex customer environments to solve architectural bottlenecks. Internally, provide mentorship to junior PMs and contribute to the maturing of PM processes within the India hub.
• Market Analysis: Keep a pulse on the ETL/ELT landscape, ensuring Celonis remains the gold standard for data extraction in the Process Intelligence category.

The qualifications you need:

• 5+ years of experience in technical product management, with a proven track record of shipping complex data-centric products.
• Deep Domain Expertise: Strong understanding of data extraction patterns (CDC, Delta-loads, Batch vs. Streaming) and protocols (REST, OData, JDBC).
• ERP/SaaS Fluency: Direct experience with enterprise ecosystems, specifically SAP (functional modules and data structures) or major Cloud platforms (AWS, Azure, GCP).
• Technical Rigor: Ability to hold your own in architectural discussions with Staff Engineers while simplifying those concepts for C-level executives.
• Analytical Mindset: You love data and use it to drive decisions. Whether it’s analyzing feature adoption or optimizing extractor throughput.
• Entrepreneurial Spirit: You are excited about the challenge of being a foundational member of a new engineering hub, bringing clarity to ambiguity and building a high-performance culture.
• Communication Excellence: Exceptional ability to influence without authority and tell a compelling story about the "why" behind the "what."

Nice to have:

• Advanced degree in Computer Science, Engineering, or Business is highly desirable to connect technical performance to broad business outcomes and enterprise ROI.
•  Proven experience in designing AI-driven user journeys, specifically leveraging Agentic Workflows to automate technical complexities.
• Familiarity or experience with tools like Fivetran, Airbyte, Databricks, or Snowflake.

Title: Principal Data Software Engineer

Location: Bengaluru (Bangalore)

Opportunity:

Get Well is seeking a visionary and technically adept Principal Data Software Engineer to design, develop and optimize our cloud-native data platform supporting AI, analytics, and clinical applications. This role is pivotal in architecting scalable, secure, and high-performance data processing systems within a regulated healthcare environment. 

The ideal candidate brings deep technical expertise in data engineering, data governance, cloud infrastructure and hands-on experience with healthcare data standards, EMR integration, and clinical ontologie. The candidate should have a proven record of building secure, scalable data platforms. This position reports to the Senior Director, Product Development. This role requires close collaboration with data engineers, product teams, AI engineers and compliance specialists to deliver accurate, accessible, and actionable data solutions.

Responsibilities:

Platform Architecture & Design

• Design and implement scalable, secure, and efficient data architectures (e.g., data lakehouse, medallion architecture) to support enterprise AI and analytics initiatives.
• Define technical specifications for data ingestion, transformation, storage, and access layers.
• Evaluate and recommend tools, frameworks, and cloud infrastructure to optimize performance, scalability, and cost-efficiency.
• Ensure architectural alignment with organizational AI, analytics, and clinical application goals.

Data Engineering & Operations

• Develop and maintain high-performance data pipelines for both batch and streaming data processing, leveraging tools such as Apache Spark, Databricks or Snowflake.
• Implement deployment and orchestration frameworks (e.g., Airflow, dbt, Spark, Databricks, Snowflake)
• Adhere to engineering best practices for CI/CD, observability, incident response, and SLA adherence
• Optimize data processing systems for performance, reliability, and reusability.

• Mentor engineers to foster technical growth and ensure alignment with best practices in data engineering.

Governance, Quality & Compliance

• Collaborate with data governance and compliance teams to implement data security, encryption, and access control policies in line with HIPAA, GDPR, and other regulations.
• Ensure data quality through validation, lineage tracking, and metadata management practices.
• Support the development and maintenance of data catalogs for discoverability and stewardship

Collaboration & Technical Leadership

• Partner with data engineers, product teams, and clinical informatics specialists to deliver integrated data solutions.
• Provide technical guidance and mentorship to junior engineers, fostering a culture of technical excellence and collaboration.
• Communicate complex technical designs and solutions to both technical and non-technical stakeholders effectively.
• Contribute to agile development practices, participating in code reviews, design discussions, and continuous improvement initiatives.

Innovation & Technical Expertise

• Stay informed about emerging trends in data engineering, cloud-native architectures, and healthcare data standards.
• Prototype and evaluate modern data frameworks and tools (e.g., Delta Lake, Apache Iceberg) to enhance platform capabilities.
• Communicate complex technical concepts to both technical and non-technical stakeholders.
• Advocate for best practices in data platform design to ensure scalability, explainability, and compliance in AI-driven systems.

Requirements:

Education & Experience

• Bachelor’s or Master’s degree in Computer Science or related technical discipline
• 12+ years of experience with at least 4+ years in data engineering or platform roles
• Proven track record of designing and implementing cloud-native data processing systems.

Technical Proficiency

• Advanced proficiency in Python, Scala, SQL, and distributed data processing frameworks such as Apache Spark.
• Hands-on experience with cloud-based data platforms (e.g., Databricks, Snowflake, BigQuery, or Redshift).
• Demonstrated ability to transform raw clinical data into curated, ML-ready datasets for analytics and AI applications.
• Hands-on expertise in healthcare data standards including FHIR, HL7, USCDI, and CCDA

Professional Skills

• Strong problem-solving skills with a focus on delivering scalable and maintainable solutions.
• Excellent collaboration and communication skills, with the ability to work effectively in cross-functional teams.
• Proactive, detail-oriented, and committed to driving technical excellence in a fast-paced environment.

About Get Well:

Now part of the SAI Group family, Get Well is redefining digital patient engagement by putting patients in control of their personalized healthcare journeys, both inside and outside the hospital. Get Well is combining high-tech AI navigation with high-touch care experiences driving patient activation, loyalty, and outcomes while reducing the cost of care. For almost 25 years, Get Well has served more than 10 million patients per year across over 1,000 hospitals and clinical partner sites, working to use longitudinal data analytics to better serve patients and clinicians. AI innovator SAI Group led by Chairman Romesh Wadhwani is the lead growth investor in Get Well. Get Well’s award-winning solutions were recognized again in 2024 by KLAS Research and AVIA Marketplace. Learn more at Get Well and follow-us on LinkedIn and Twitter.

Get Well is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.

About SAI Group:

• SAIGroup commits to $1 Billion capital, an advanced AI platform that currently processes 300M+ patients, and 4000+ global employee base to solve enterprise AI and high priority healthcare problems. SAIGroup - Growing companies with advanced AI; https://www.cnbc.com/2023/12/08/75-year-old-tech-mogul-betting-1-billion-of-his-fortune-on-ai-future.html
• Bio of our Chairman Dr. Romesh Wadhwani: Team - SAIGroup (Informal at Romesh Wadhwani - Wikipedia)
• TIME Magazine recently recognized Chairman Romesh Wadhwani as one of the Top 100 AI leaders in the world - Romesh and Sunil Wadhwani: The 100 Most Influential People in AI 2023 | TIME

Opportunity

Get Well is hiring a highly motivated Senior Data Software Engineer to help build and scale our modern cloud-native data platform that supports AI, analytics, and clinical applications. You'll focus on developing robust and compliant data processing workflows while working closely with platform and architecture teams to operationalize next-generation, healthcare-specific data systems.

This role is ideal for an experienced engineer passionate about transforming complex healthcare data into meaningful applications through engineering excellence, collaboration, and innovation. You will play a key role in the continued growth of our data platform and help ensure that our data systems are secure, reliable, and high-performing within the healthcare industry. 

Candidates must have hands-on software development experience with at least one healthcare company—preferably in the provider space—with exposure to EHRs and core healthcare data domains.

Responsibilities

Data Engineering & Pipeline Development

• Design, implement, and maintain scalable batch and real-time data pipelines across a variety of sources and formats.
• Develop high-performance ETL/ELT workflows using tools and frameworks such as Apache Spark, Databricks, dbt, and Snowflake.
• Collaborate with Staff Engineers and Architects to translate platform architecture into executable, maintainable solutions.
• Automate data orchestrations using Airflow or other workflow managers to enable continuous data processing and delivery.

Healthcare Data Integration & Compliance

• Ingest and normalize healthcare datasets (e.g., EHR, FHIR, HL7, CCDA, Claims) in accordance with internal data models.
• Work with governance and compliance teams to meet regulatory requirements including HIPAA and GDPR.
• Implement best practices for encryption, data masking, access control, and auditability across the platform.
• Support efforts around metadata management, data lineage, and structured logging for traceability and transparency.

Platform Optimization & Technical Execution

• Tune Spark-based pipelines and SQL transformations for performance, reliability, and resource efficiency.
• Participate in code reviews, unit testing, and CI/CD processes to ensure code quality and maintainability.
• Work collaboratively across product, informatics, and DevOps teams to translate business needs into technical solutions.
• Contribute to documentation, analytics enablement, and reusability of shared platform components.

Growth, Mentorship & Best Practices

• Mentor junior engineers through code reviews, paired programming, and collaborative development practices.
• Model and advocate for engineering best practices, including clean architecture, effective testing, and proactive monitoring.
• Stay current with trends in distributed systems, cloud-native computing, data privacy, and healthcare interoperability.
• Propose and implement technical upgrades and innovative approaches based on tools like Delta Lake, Apache Iceberg, and emerging GenAI capabilities.

Qualifications

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related technical field.
• 6+ years of relevant experience in data engineering roles, with at least 3 years focused on cloud-native or large-scale data systems.
• Must have software development experience in at least one healthcare company, preferably in the provider space, with exposure to EHR systems or key healthcare data domains.
• Direct experience designing and building pipelines that move and transform healthcare data, with production-quality data quality checks at scale.

Technical Skills

• Proficient in Python, SQL, and Apache Spark for distributed processing and transformation.
• Hands-on experience with modern data platforms—such as Snowflake, Databricks, Redshift, or BigQuery.
• Deep experience working with public cloud providers, particularly Azure, including native services for data storage, processing, and orchestration (e.g., Azure Data Lake, Azure Synapse).
• Experience with orchestration tools like Airflow and transformation layers such as dbt.
• Familiar with data pipelines in regulated environments, including auditing, encryption, and compliance controls.
• amiliarity with healthcare-specific data formats (FHIR, HL7, EDI) and terminologies (ICD-10, SNOMED, LOINC).

Professional Attributes

• Strong problem-solving skills with a focus on quality, performance, and pragmatism.
• Excellent communication and teamwork skills, with the ability to work across multidisciplinary teams.
• High accountability and ownership mindset with a commitment to excellence in healthcare technology.

About GW RhythmX

GW RhythmX is revolutionizing healthcare through connected, AI-native intelligence that unites clinical insight, patient engagement, and system-wide care orchestration. The company combines market-leading AI precision care technology with extensive trusted patient engagement leadership to help health systems deliver the right care, at the right time, through the right clinician and channel. Its solutions are deployed across more than 150 health systems, touching more than 85M patients including 8M U.S. military veterans. The company's award-winning solutions were recognized again in 2024 by KLAS Research, Fierce Healthcare, and AVIA Marketplace. A SymphonyAI Group company, GW RhythmX leverages various firm assets, including $1B+ in R&D investment, longitudinal data related to 300 million patients, 4.4 billion total annual claims, and 1.8 million healthcare professionals at more than 3,000 facilities globally.

GW RhythmX  is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.

Opportunity

Get Well is seeking a skilled and motivated Software Data Engineer to help implement and scale our cloud-native data platform supporting AI, analytics, and clinical applications. This role involves building, testing, and optimizing secure and high-performance pipelines and workflows that power critical healthcare applications.

As a Software Data Engineer, you will collaborate closely with staff and senior engineers to deliver robust data infrastructure in a regulated, compliance-driven healthcare environment. You’ll gain deep exposure to modern tools and cloud technologies while contributing meaningfully to transforming healthcare delivery through data and AI.

Responsibilities

Data Engineering & Pipeline Development

• Implement and maintain reliable batch and real-time data pipelines using modern frameworks such as Apache Spark, Databricks, and Snowflake.
• Support ingestion, transformation, and delivery of structured and semi-structured data across cloud-native platforms.
• Contribute to performance tuning and optimization efforts to ensure scalable and cost-effective workflows.
• Utilize orchestration tools like Airflow, Temporal and dbt to enable automation, scheduling, monitoring, and version control of pipeline operations.

Data Quality & Compliance

• Enforce data quality through the implementation of validation checks, data lineage tracking, and schema enforcement.
• Assist in meeting healthcare compliance standards (e.g., HIPAA, GDPR) by implementing best practices for data handling, encryption, and access controls.
• Work with metadata and data cataloging systems to ensure accuracy, transparency, and discoverability of enterprise datasets.

Technical Implementation & Collaboration

• Participate in agile development practices, including daily stand-ups, sprint planning, retrospectives, and backlog grooming.
• Support code reviews and debugging efforts to uphold code reliability, reusability, and maintainability.
• Collaborate with cross-functional teams, including Data Science, Product, Quality, and Security, to deliver coordination and alignment on technical implementations.

Learning & Growth

• Stay current on evolving technologies in cloud data engineering, including tools such as Delta Lake, Iceberg, and healthcare interoperability standards.
• Actively engage in knowledge sharing and continuous learning through team discussions, peer programming, and internal demos.
• Show initiative in exploring process improvements, automation opportunities, and platform enhancements.

Qualifications

Education & Experience

• Bachelor’s degree in Computer Science, Engineering, or related field.
• 2–5 years of hands-on experience in data engineering, platform development, or software engineering focused on data systems.
• Software development experience at a healthcare company (provider space preferred), with exposure to EHR systems or healthcare data domains is strongly preferred.

Technical Skills

• Proficiency in Python and SQL for building and maintaining data workflows.
• Experience working with distributed data frameworks like Apache Spark or Databricks.
• Familiarity with data orchestration tools such as Airflow, Temporal and data modeling tools like dbt.
• Experience with data platforms such as Azure data factory, databricks, etc.
• Exposure to cloud providers - Azure preferred.
• Exposure to healthcare data types (e.g., FHIR, HL7, CCDA) and terminologies (e.g., ICD, SNOMED) is a strong plus.

Professional Attributes

• Strong analytical and problem-solving skills with attention to performance and reliability.
• Effective communicator and team player who thrives in collaborative, cross-functional settings.
• Eagerness to learn new tools and technologies and contribute to platform evolution in a fast-paced environment.

About GW RhythmX

GW RhythmX is revolutionizing healthcare through connected, AI-native intelligence that unites clinical insight, patient engagement, and system-wide care orchestration. The company combines market-leading AI precision care technology with extensive trusted patient engagement leadership to help health systems deliver the right care, at the right time, through the right clinician and channel. Its solutions are deployed across more than 150 health systems, touching more than 85M patients including 8M U.S. military veterans. The company's award-winning solutions were recognized again in 2024 by KLAS Research, Fierce Healthcare, and AVIA Marketplace. A SymphonyAI Group company, GW RhythmX leverages various firm assets, including $1B+ in R&D investment, longitudinal data related to 300 million patients, 4.4 billion total annual claims, and 1.8 million healthcare professionals at more than 3,000 facilities globally.

GW RhythmX  is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.

Who are we and What do we do? 

InMobi is the largest independent mobile advertising network in the world. Building a new company in 2007 was no ordinary task. As the recession hit, the iPhone was born and launched a revolution. Mobile advertising wasn’t yet a thing, other than SMS, and venture capital funding was hard to come by for four guys in India.  Yet with passion, foresight, and conviction – InMobi charted its own course, helping to transform the way consumers engage with their phones and create today's booming app economy wherein consumers now spend 4.2 hours per day.  After fourteen years of innovation, our end-to-end advertising software platform, connected content and commerce experiences have formed a powerful engine for growth that activates audiences, drives real connections, and diversifies revenue for companies around the world. Our global organization of InMobians are excited to continue discovering and developing impactful technologies that will continue to transform people, businesses, and society. With offices on five continents, InMobi provides advertisers, publishers and developers with a uniquely global solution for advertising. The network is growing and now delivers the unprecedented ability to reach 1.64 billion devices, in over 165 countries, through more than 200 billion mobile ad impressions monthly. The company has over 17 offices including Bangalore (HQ), London, New York, Paris, San Francisco, Shanghai, Beijing, Seoul, Singapore, Tokyo and Dubai. 
For more information, please visit http://www.inmobi.com 

 
What’s the InMobi family like?

Consistently featured among the “Great Places to Work” in India since 2017, our culture is our true north, enabling us to think big, solve complex challenges and grow with new opportunities. InMobians are passionate and driven, creative and fun-loving, take ownership and are results focused. We invite you to free yourself, dream big and chase your passion. 

 
What do we promise?

We offer an opportunity to have an immediate impact on the company and our business. The work that you shall do will be mission critical for InMobi and will be critical for optimizing tech operations, working with highly capable and ambitious peer groups. At InMobi, you get food for your body, soul, and mind with daily meals, gym, and yoga classes, cutting-edge training and tools, cocktails at drink cart Thursdays and fun at work on Funky Fridays. We even promise to let you bring your kids and pets to work. 

About the Role

The Global Business Analytics & Insights team is evolving from a traditional reporting function into an AI-powered, agentic intelligence layer that drives autonomous, real-time decision-making across the organisation.

As a Lead Business Intelligence Analyst, you will play a critical role in this transformation — moving beyond dashboards to build intelligent, self-serve, and eventually self-driving analytics systems.

You will own the design and evolution of next-generation BI systems that:

• Not only describe what happened, but explain why it happened
• Recommend what to do next
• And ultimately enable automated, agent-driven decision workflows

This role sits at the intersection of analytics, data products, and AI, and requires someone who can combine business intuition, technical depth, and product thinking to reimagine how data is consumed and decisions are made across GTM teams.

You will work closely with Strategy & Operations, Product, Data Engineering, and GTM leadership to build an intelligence layer that powers the full customer journey — from Marketing to Revenue realization.

What You’ll Be Doing?

Build the Intelligence Layer (Beyond Dashboards)

• Design and own scalable BI frameworks that evolve from dashboards → insights → recommendations → automated actions
• Develop semantic layers and metric definitions that standardize decision-making across teams
• Move the org from “report consumption” to decision intelligence systems

Drive Agentic BI Vision

• Help define and execute the roadmap toward agentic BI (AI agents answering business questions autonomously)
• Build use cases where:
  • Business questions are translated into queries automatically
  • Insights are generated proactively (not reactively)
  • Outputs are delivered via conversational interfaces (Teams, email, etc.)
• Partner in building AI-powered analytics agents on top of Databricks / warehouse layers

Advanced Analytics & Decision Systems

• Build models to:
  • Forecast revenue and pipeline health
  • Detect anomalies and trigger alerts
  • Identify drivers of growth and inefficiencies
• Develop leading indicator frameworks and early warning systems for GTM performance

Insight Generation & Storytelling

• Go beyond reporting to:
  • Identify root causes of business trends
  • Translate data into clear, actionable recommendations
• Support leadership with narrative-driven insights, not just metrics

Data Product & Self-Serve Enablement

• Build self-serve analytics experiences tailored to different personas (Sales, Strategy, Leadership)
• Reduce dependency on analysts by enabling intuitive, trustworthy data access
• Drive adoption of “review via dashboards” → “review via intelligent systems”

Data Integrity & System Thinking

• Work with Data Products to ensure data quality across systems (Salesforce, Databricks, BI tools)
• Investigate discrepancies and build robust data governance mechanisms
• Work with data engineering to ensure clean, reliable, and scalable pipelines

Cross-functional Leadership

• Partner with:
  • GTM teams (Marketing, Sales)
  • GTM enablement teams (Strategy, Revenue Operations, Finance)
  • Product & Marketplace teams
• Influence decision-making at multiple levels through data-backed narratives

Automation & Efficiency

Continuously identify opportunities to:

• Automate reporting workflows
• Eliminate redundant analysis
• Build reusable analytics assets

Who You Are

Analytical & Structured Thinker

You don’t just analyze data — you frame problems, test hypotheses, and drive decisions.

Builder Mindset (Not Just Consumer of BI)

You’ve built systems — dashboards, data models, or analytics products — and want to reimagine BI as a product, not a service.

AI-Forward Thinker

You are excited about using:

• LLMs
• AI agents
• Automation frameworks

to fundamentally change how analytics is delivered.

Business-Oriented

You understand that the goal is not dashboards — it’s revenue impact, efficiency, and growth.

Comfortable with Ambiguity

You thrive in 0→1 environments and can bring structure to undefined problems.

What We’re Looking For

Core Skills

• Strong SQL and experience working with large-scale datasets (Databricks, BigQuery, Snowflake, etc.)
• Experience with BI tools (Power BI, Tableau, Looker)
• Strong analytical thinking: root cause analysis, hypothesis testing, problem structuring
• Experience building end-to-end analytics solutions

Preferred Experience

• 4–8 years in analytics / BI / RevOps / strategy roles
• Experience working with GTM / revenue teams
• Exposure to data modeling and metric design
• Experience with Python / statistical modeling / forecasting

Strong Plus

• Experience or interest in:
  • AI/ML applications in analytics
  • Conversational BI / NLQ systems
  • Building internal data products
• Prior AdTech / Marketplace experience

What Success Looks Like in This Role

• The organization moves from: Static dashboards → dynamic, insight-driven systems
• Stakeholders shift from: Asking analysts → self-serve + AI-assisted decision making
• BI evolves into: A central intelligence layer powering GTM strategy

Why This Role is Unique

This is not a traditional BI role.

You will be helping build:

• One of the first agentic BI ecosystems in AdTech
• A system that connects data → intelligence → action
• A foundation for AI-driven decision-making across the company

Why Join Us?

We value autonomy, collaboration, technical innovation, and results-oriented thinking. InMobi’s culture is all about rewarding excellence so there are fantastic opportunities for the right candidates.

Why project44?  

At project44, we believe in better.  

We challenge the status quo because we know a better supply chain isn’t just possible—it’s essential. Better for our customers. Better for their business. Better for the world.  

With our Decision Intelligence Platform, Movement, we’re redefining how global supply chains operate. By transforming fragmented logistics data into real-time, AI-powered insights, we empower companies to connect instantly, see clearly, act decisively, and automate intelligently. Our Supply Chain AI enhances visibility, drives smarter execution, and unlocks next-gen applications that keep businesses moving forward.  

Headquartered in Chicago, IL with a 2nd HQ in Bengaluru, India we are powered by a diverse global team that is tackling the toughest logistics challenges with innovation, urgency, and purpose.  

If you’re driven to solve meaningful problems, leverage AI to scale rapidly, drive impact daily, and be part of a high-performance team – we should talk. 

Description:    

project44 is looking for a Staff Data Scientist to join our engineering team. You will work in a fast-paced Agile environment designing, building, and implementing best-in-class integrations to accelerate how project44 connects to the world’s logistics networks.   

About the Role

• Staff Data Scientist to lead the development of next-generation AI/ML systems at Project44, spanning ETA, risk, anomaly detection, and supply chain intelligence. This role sits at the intersection of applied modeling, platform thinking, and production impact, with a mandate to both ship high-value ML capabilities and build reusable Data Science platform primitives that scale across teams.
• In addition, this role will drive the integration of Generative AI, LLMs, and agentic systems into core workflows—enabling reasoning-driven diagnostics, automation, and intelligent decision support across the supply chain.
• You will work closely with Data Science, ML Engineering, Data Engineering, Platform, and Product teams to deliver production-grade systems and establish a scalable, repeatable approach to AI development at P44.

What You’ll Do

• Drive High-Impact ML Systems Lead end-to-end development of models for ETA, risk, anomaly, and fraud—leveraging advanced techniques (embeddings, transformers, hybrid models).
• Build Data Science as a Platform Develop reusable ML infrastructure (features, experimentation, deployment, monitoring) to scale model development and reduce time-to-production.
• Lead GenAI & Agentic Systems Build LLM-powered solutions (RAG, diagnostics, automation, coding agents) and establish guardrails, evaluation, and explainability.
• Translate Business Problems into ML Solutions Convert customer workflows into well-defined ML problems and ensure measurable business impact.
• Drive Experimentation & Evaluation Establish strong offline/online evaluation frameworks tied to business outcomes.
• Collaborate Across Engineering Partner with MLE and DE to build scalable, reliable systems across the ML lifecycle.

What We’re Looking For

• Experience 8–10+ years in Data Science / Applied ML with a strong track record of building and deploying production-grade ML systems.
• Core Modeling & Technical Expertise Deep expertise across tree-based models, transformers, probabilistic modeling, and feature engineering, with a strong data-centric mindset.
• Data & Platform Fluency Proficient in SQL and Python, with hands-on experience in modern data platforms (Snowflake/Databricks), pipelines (Spark, Airflow), streaming systems (Kafka), and MLOps tooling.
• GenAI & LLM Capability Experience building RAG systems, working with embeddings and vector databases, and developing LLM-based applications and agentic workflows. Strong understanding of evaluation, guardrails, and safe deployment of GenAI systems.
• Systems & Engineering Mindset Familiarity with distributed systems, APIs, and deployment patterns, with the ability to write clean, production-quality code.
• Analytical Rigor & Diagnostics Strong ability to evaluate model performance, detect edge cases, run root cause analysis, and design robust monitoring and evaluation frameworks.
• Data Quality & Signal Awareness Experience handling messy, real-world data, including drift, bias, missingness, and anomalies, along with tools and techniques to detect and address these issues.
• Modeling Judgment & Trade-offs Ability to identify when to use ML versus heuristics and design pragmatic hybrid solutions. Strong understanding of architectural trade-offs across models and systems.
• Business Impact Orientation Clear understanding of how ML metrics translate to business outcomes, with the ability to balance trade-offs across accuracy, scalability, latency, and customer experience.
• Leadership & Communication Strong problem framing, stakeholder influence, and ability to communicate model behavior and decisions clearly to both technical and non-technical audiences. Proven track record of driving measurable business impact.

Preferred Skills

• Experience in logistics (Ocean, Truckload), supply chain, or high-volume operational systems
• Experience with geospatial data, routing, and tracking systems
• Experience with anomaly detection, fraud modeling, ETA prediction
• Experience building internal platforms or tools for DS teams

What Success Looks Like (6–12 Months)

• Deliver 2 high-impact ML capabilities with measurable customer value
• Establish standardized experimentation, monitoring, and RCA workflows
• Introduce GenAI/agentic capabilities that improve productivity and insight generation
• Reduce time-to-production and increase reuse across DS teams
• Drive measurable improvements in model performance and system reliability

In-office Commitment: This position requires a commitment to contribute to our collaborative culture by working in-office three days weekly. 

Diversity & Inclusion 

At project44, we're designing the future of how the world moves and is connected through trade and global supply chains. As we work to deliver a truly world-class product and experience, we are also intentionally building teams that reflect the unique communities we serve. We’re focused on creating a company where all team members can bring their authentic selves to work every day. 

We’re building a company that every one of us at project44 is proud to work for, and our journey of becoming a more diverse, equitable and inclusive organization, where all have a sense of belonging, is shaped through the actions of our leadership, global teams, and individual team members. We are resolute in our belief that each team member has an equal responsibility to mold and uphold our culture. 

project44 is an equal opportunity employer seeking to enrich our work environment by creating opportunities for individuals of all backgrounds and experiences to thrive. If you share our values and our passion for helping the way the world moves, we’d love to review your application! 

For any accommodation needed during the hiring process, please email   recruiting@project44.com. Even if you don’t meet 100% of the above job description you should still seriously consider applying. Studies show that you can still be considered for a role if you meet just 50% of the role’s requirements. 

More about project44 

Since 2014, project44 has been transforming the way one of the largest, most important global industries does business. As transportation and logistics continue to evolve and customer expectations around delivery become more demanding, industry technology must rise to the occasion. In just a few short years, we have created a digital infrastructure that eliminates the inefficiencies caused by dated technology and manual processes. Our Advanced Visibility Platform is used by the world’s leading brands to track shipments, collaborate with supply chain partners, drive operational efficiencies, and create outstanding customer experiences. 

Why project44?  

At project44, we believe in better.  

We challenge the status quo because we know a better supply chain isn’t just possible—it’s essential. Better for our customers. Better for their business. Better for the world.  

With our Decision Intelligence Platform, Movement, we’re redefining how global supply chains operate. By transforming fragmented logistics data into real-time, AI-powered insights, we empower companies to connect instantly, see clearly, act decisively, and automate intelligently. Our Supply Chain AI enhances visibility, drives smarter execution, and unlocks next-gen applications that keep businesses moving forward.  

Headquartered in Chicago, IL with a 2nd HQ in Bengaluru, India we are powered by a diverse global team that is tackling the toughest logistics challenges with innovation, urgency, and purpose.  

If you’re driven to solve meaningful problems, leverage AI to scale rapidly, drive impact daily, and be part of a high-performance team – we should talk. 

Description:    

project44 is looking for a Staff Data Engineer to join our engineering team. You will work in a fast-paced Agile environment designing, building, and implementing best-in-class integrations to accelerate how project44 connects to the world’s logistics networks.   

About the Role

We are looking for a Staff Data Engineer to drive the execution and scaling of project44’s data platform.This role sits at the intersection of Data Engineering, Data Science, and Product, with a mandate to translate architectural vision into reliable, scalable systems used across teams.

You will partner closely with other data engineers to implement platform direction, establish engineering standards, and ensure consistent, high-quality execution across data systems. Your focus will be on solving complex data challenges, driving adoption of best practices, and enabling teams to build efficiently on a shared foundation.

As AI reshapes how data systems operate, you will also help integrate agentic and GenAI-powered workflows into data pipelines and developer workflows—improving automation, observability, and system intelligence.

What You’ll Do

Drive Platform Execution

• Translate architectural direction into production-grade systems across ingestion, transformation, and serving layers.

Establish Standards & Best Practices

• Define and enforce patterns for data modeling, pipeline design, observability, testing, and data quality across teams.

Solve Complex Data Problems

• Own and resolve high-impact technical challenges related to scale, latency, reliability, and cost efficiency.

Enable Consistency Across Teams

• Work across multiple teams to drive adoption of shared data models, tooling, and engineering practices.

Build Scalable Data Systems

• Develop and optimize pipelines and data systems for performance, maintainability, and long-term scalability.

Integrate AI-Native Workflows

• Implement agentic and GenAI-driven workflows to automate data operations, improve monitoring, and accelerate development.

Mentor & Raise the Bar

• Act as a technical leader within the team, mentoring junior engineers and elevating engineering quality across the organization.

What We’re Looking For

8–10+ years in Data Engineering or Software Engineering, with a strong track record of building and scaling production-grade systems.

Technical Expertise

• Strong programming skills (Python preferred, Java/Scala a plus) and deep experience with modern data technologies (Spark, Snowflake, Databricks).

Data Systems & Execution

• Proven ability to build and operate reliable, scalable data pipelines and systems in production environments.

Data Modeling & Warehousing

• Strong experience in data modeling, warehousing, and building analytics- and ML-ready datasets.

Distributed Systems & Trade-offs

• Ability to navigate trade-offs across performance, cost, reliability, and scalability in cloud-native systems.

AI & Modern Tooling

• Experience leveraging GenAI or agentic tools to improve developer productivity, automate workflows, or enhance data systems.

Cross-Team Influence

• Experience working across teams to drive alignment, adoption of standards, and consistent execution.

Communication & Leadership

• Strong communication skills and the ability to influence technical decisions across teams.

Preferred Skills

• Experience with real-time and event-driven systems (Kafka, streaming architectures)
• Familiarity with orchestration tools (Airflow, Argo) and containerization (Docker, Kubernetes)
• Experience with data governance and access control (RBAC)
• Exposure to analytics and BI tools (Looker, Tableau)
• Experience building shared data platforms or internal tooling
• Background in logistics, supply chain, or high-scale operational systems

What Success Looks Like (6–12 Months)

• Successfully implemented core data platform patterns across multiple teams
• Improved data reliability, observability, and quality in critical pipelines
• Reduced inconsistency in data models and engineering practices across teams
• Enabled faster development and deployment of data and ML workflows
• Introduced AI-driven improvements in data workflows and developer productivity
• Acted as a key technical leader, raising the bar for execution and engineering quality

In-office Commitment: This position requires a commitment to contribute to our collaborative culture by working in-office three days weekly. 

Diversity & Inclusion 

At project44, we're designing the future of how the world moves and is connected through trade and global supply chains. As we work to deliver a truly world-class product and experience, we are also intentionally building teams that reflect the unique communities we serve. We’re focused on creating a company where all team members can bring their authentic selves to work every day. 

We’re building a company that every one of us at project44 is proud to work for, and our journey of becoming a more diverse, equitable and inclusive organization, where all have a sense of belonging, is shaped through the actions of our leadership, global teams, and individual team members. We are resolute in our belief that each team member has an equal responsibility to mold and uphold our culture. 

project44 is an equal opportunity employer seeking to enrich our work environment by creating opportunities for individuals of all backgrounds and experiences to thrive. If you share our values and our passion for helping the way the world moves, we’d love to review your application! 

For any accommodation needed during the hiring process, please email   recruiting@project44.com. Even if you don’t meet 100% of the above job description you should still seriously consider applying. Studies show that you can still be considered for a role if you meet just 50% of the role’s requirements. 

More about project44 

Since 2014, project44 has been transforming the way one of the largest, most important global industries does business. As transportation and logistics continue to evolve and customer expectations around delivery become more demanding, industry technology must rise to the occasion. In just a few short years, we have created a digital infrastructure that eliminates the inefficiencies caused by dated technology and manual processes. Our Advanced Visibility Platform is used by the world’s leading brands to track shipments, collaborate with supply chain partners, drive operational efficiencies, and create outstanding customer experiences. 

Why project44?  

At project44, we believe in better.  

We challenge the status quo because we know a better supply chain isn’t just possible—it’s essential. Better for our customers. Better for their business. Better for the world.  

With our Decision Intelligence Platform, Movement, we’re redefining how global supply chains operate. By transforming fragmented logistics data into real-time, AI-powered insights, we empower companies to connect instantly, see clearly, act decisively, and automate intelligently. Our Supply Chain AI enhances visibility, drives smarter execution, and unlocks next-gen applications that keep businesses moving forward.  

Headquartered in Chicago, IL with a 2nd HQ in Bengaluru, India we are powered by a diverse global team that is tackling the toughest logistics challenges with innovation, urgency, and purpose.  

If you’re driven to solve meaningful problems, leverage AI to scale rapidly, drive impact daily, and be part of a high-performance team – we should talk. 

Description:    

project44 is looking for a Staff Machine Learning Engineer to join our engineering team. You will work in a fast-paced Agile environment designing, building, and implementing best-in-class integrations to accelerate how project44 connects to the world’s logistics networks.   

About the Role

• Staff ML Engineerto lead the development of next-generation AI/ML systems at Project44, spanning ETA, risk, anomaly detection, and supply chain intelligence. This role sits at the intersection of applied modeling, platform thinking, and production impact, with a mandate to both ship high-value ML capabilities and build reusable Data Science platform primitives that scale across teams.
• In addition, this role will drive the integration of Generative AI, LLMs, and agentic systems into core workflows—enabling reasoning-driven diagnostics, automation, and intelligent decision support across the supply chain.
• You will work closely with Data Science, ML Engineering, Data Engineering, Platform, and Product teams to deliver production-grade systems and establish a scalable, repeatable approach to AI development at P44.

What You’ll Do

• Drive High-Impact ML Systems Lead end-to-end development of models for ETA, risk, anomaly, and fraud—leveraging advanced techniques (embeddings, transformers, hybrid models).
• Build Data Science as a Platform Develop reusable ML infrastructure (features, experimentation, deployment, monitoring) to scale model development and reduce time-to-production.
• Lead GenAI & Agentic Systems Build LLM-powered solutions (RAG, diagnostics, automation, coding agents) and establish guardrails, evaluation, and explainability.
• Translate Business Problems into ML Solutions Convert customer workflows into well-defined ML problems and ensure measurable business impact.
• Drive Experimentation & Evaluation Establish strong offline/online evaluation frameworks tied to business outcomes.
• Collaborate Across Engineering Partner with MLE and DE to build scalable, reliable systems across the ML lifecycle.

What We’re Looking For

• Experience 8–10+ years in Data Science / Applied ML with a strong track record of building and deploying production-grade ML systems.
• Core Modeling & Technical Expertise Deep expertise across tree-based models, transformers, probabilistic modeling, and feature engineering, with a strong data-centric mindset.
• Data & Platform Fluency Proficient in SQL and Python, with hands-on experience in modern data platforms (Snowflake/Databricks), pipelines (Spark, Airflow), streaming systems (Kafka), and MLOps tooling.
• GenAI & LLM Capability Experience building RAG systems, working with embeddings and vector databases, and developing LLM-based applications and agentic workflows. Strong understanding of evaluation, guardrails, and safe deployment of GenAI systems.
• Systems & Engineering Mindset Familiarity with distributed systems, APIs, and deployment patterns, with the ability to write clean, production-quality code.
• Analytical Rigor & Diagnostics Strong ability to evaluate model performance, detect edge cases, run root cause analysis, and design robust monitoring and evaluation frameworks.
• Data Quality & Signal Awareness Experience handling messy, real-world data, including drift, bias, missingness, and anomalies, along with tools and techniques to detect and address these issues.
• Modeling Judgment & Trade-offs Ability to identify when to use ML versus heuristics and design pragmatic hybrid solutions. Strong understanding of architectural trade-offs across models and systems.
• Business Impact Orientation Clear understanding of how ML metrics translate to business outcomes, with the ability to balance trade-offs across accuracy, scalability, latency, and customer experience.
• Leadership & Communication Strong problem framing, stakeholder influence, and ability to communicate model behavior and decisions clearly to both technical and non-technical audiences. Proven track record of driving measurable business impact.

Preferred Skills

• Experience in logistics (Ocean, Truckload), supply chain, or high-volume operational systems
• Experience with geospatial data, routing, and tracking systems
• Experience with anomaly detection, fraud modeling, ETA prediction
• Experience building internal platforms or tools for DS teams

What Success Looks Like (6–12 Months)

• Deliver 2 high-impact ML capabilities with measurable customer value
• Establish standardized experimentation, monitoring, and RCA workflows
• Introduce GenAI/agentic capabilities that improve productivity and insight generation
• Reduce time-to-production and increase reuse across DS teams
• Drive measurable improvements in model performance and system reliability

In-office Commitment: This position requires a commitment to contribute to our collaborative culture by working in-office three days weekly. 

Diversity & Inclusion 

At project44, we're designing the future of how the world moves and is connected through trade and global supply chains. As we work to deliver a truly world-class product and experience, we are also intentionally building teams that reflect the unique communities we serve. We’re focused on creating a company where all team members can bring their authentic selves to work every day. 

We’re building a company that every one of us at project44 is proud to work for, and our journey of becoming a more diverse, equitable and inclusive organization, where all have a sense of belonging, is shaped through the actions of our leadership, global teams, and individual team members. We are resolute in our belief that each team member has an equal responsibility to mold and uphold our culture. 

project44 is an equal opportunity employer seeking to enrich our work environment by creating opportunities for individuals of all backgrounds and experiences to thrive. If you share our values and our passion for helping the way the world moves, we’d love to review your application! 

For any accommodation needed during the hiring process, please email   recruiting@project44.com. Even if you don’t meet 100% of the above job description you should still seriously consider applying. Studies show that you can still be considered for a role if you meet just 50% of the role’s requirements. 

More about project44 

Since 2014, project44 has been transforming the way one of the largest, most important global industries does business. As transportation and logistics continue to evolve and customer expectations around delivery become more demanding, industry technology must rise to the occasion. In just a few short years, we have created a digital infrastructure that eliminates the inefficiencies caused by dated technology and manual processes. Our Advanced Visibility Platform is used by the world’s leading brands to track shipments, collaborate with supply chain partners, drive operational efficiencies, and create outstanding customer experiences. 

Why project44?  

At project44, we believe in better.  

We challenge the status quo because we know a better supply chain isn’t just possible—it’s essential. Better for our customers. Better for their business. Better for the world.  

With our Decision Intelligence Platform, Movement, we’re redefining how global supply chains operate. By transforming fragmented logistics data into real-time, AI-powered insights, we empower companies to connect instantly, see clearly, act decisively, and automate intelligently. Our Supply Chain AI enhances visibility, drives smarter execution, and unlocks next-gen applications that keep businesses moving forward.  

Headquartered in Chicago, IL with a 2nd HQ in Bengaluru, India we are powered by a diverse global team that is tackling the toughest logistics challenges with innovation, urgency, and purpose.  

If you’re driven to solve meaningful problems, leverage AI to scale rapidly, drive impact daily, and be part of a high-performance team – we should talk. 

Description:    

project44 is looking for a Senior Data Scientist to join our engineering team. You will work in a fast-paced Agile environment designing, building, and implementing best-in-class integrations to accelerate how project44 connects to the world’s logistics networks.   

About the Role

• Senior Data Scientist to lead the development of next-generation AI/ML systems at Project44, spanning ETA, risk, anomaly detection, and supply chain intelligence. This role sits at the intersection of applied modeling, platform thinking, and production impact, with a mandate to both ship high-value ML capabilities and build reusable Data Science platform primitives that scale across teams.
• In addition, this role will drive the integration of Generative AI, LLMs, and agentic systems into core workflows—enabling reasoning-driven diagnostics, automation, and intelligent decision support across the supply chain.
• You will work closely with Data Science, ML Engineering, Data Engineering, Platform, and Product teams to deliver production-grade systems and establish a scalable, repeatable approach to AI development at P44.

What You’ll Do

• Drive High-Impact ML Systems Lead end-to-end development of models for ETA, risk, anomaly, and fraud—leveraging advanced techniques (embeddings, transformers, hybrid models).
• Build Data Science as a Platform Develop reusable ML infrastructure (features, experimentation, deployment, monitoring) to scale model development and reduce time-to-production.
• Lead GenAI & Agentic Systems Build LLM-powered solutions (RAG, diagnostics, automation, coding agents) and establish guardrails, evaluation, and explainability.
• Translate Business Problems into ML Solutions Convert customer workflows into well-defined ML problems and ensure measurable business impact.
• Drive Experimentation & Evaluation Establish strong offline/online evaluation frameworks tied to business outcomes.
• Collaborate Across Engineering Partner with MLE and DE to build scalable, reliable systems across the ML lifecycle.

What We’re Looking For

• Experience 5+ years in Data Science / Applied ML with a strong track record of building and deploying production-grade ML systems.
• Core Modeling & Technical Expertise Deep expertise across tree-based models, transformers, probabilistic modeling, and feature engineering, with a strong data-centric mindset.
• Data & Platform Fluency Proficient in SQL and Python, with hands-on experience in modern data platforms (Snowflake/Databricks), pipelines (Spark, Airflow), streaming systems (Kafka), and MLOps tooling.
• GenAI & LLM Capability Experience building RAG systems, working with embeddings and vector databases, and developing LLM-based applications and agentic workflows. Strong understanding of evaluation, guardrails, and safe deployment of GenAI systems.
• Systems & Engineering Mindset Familiarity with distributed systems, APIs, and deployment patterns, with the ability to write clean, production-quality code.
• Analytical Rigor & Diagnostics Strong ability to evaluate model performance, detect edge cases, run root cause analysis, and design robust monitoring and evaluation frameworks.
• Data Quality & Signal Awareness Experience handling messy, real-world data, including drift, bias, missingness, and anomalies, along with tools and techniques to detect and address these issues.
• Modeling Judgment & Trade-offs Ability to identify when to use ML versus heuristics and design pragmatic hybrid solutions. Strong understanding of architectural trade-offs across models and systems.
• Business Impact Orientation Clear understanding of how ML metrics translate to business outcomes, with the ability to balance trade-offs across accuracy, scalability, latency, and customer experience.
• Leadership & Communication Strong problem framing, stakeholder influence, and ability to communicate model behavior and decisions clearly to both technical and non-technical audiences. Proven track record of driving measurable business impact.

Preferred Skills

• Experience in logistics (Ocean, Truckload), supply chain, or high-volume operational systems
• Experience with geospatial data, routing, and tracking systems
• Experience with anomaly detection, fraud modeling, ETA prediction
• Experience building internal platforms or tools for DS teams

What Success Looks Like (6–12 Months)

• Deliver 2 high-impact ML capabilities with measurable customer value
• Establish standardized experimentation, monitoring, and RCA workflows
• Introduce GenAI/agentic capabilities that improve productivity and insight generation
• Reduce time-to-production and increase reuse across DS teams
• Drive measurable improvements in model performance and system reliability

In-office Commitment: This position requires a commitment to contribute to our collaborative culture by working in-office three days weekly. 

Diversity & Inclusion 

At project44, we're designing the future of how the world moves and is connected through trade and global supply chains. As we work to deliver a truly world-class product and experience, we are also intentionally building teams that reflect the unique communities we serve. We’re focused on creating a company where all team members can bring their authentic selves to work every day. 

We’re building a company that every one of us at project44 is proud to work for, and our journey of becoming a more diverse, equitable and inclusive organization, where all have a sense of belonging, is shaped through the actions of our leadership, global teams, and individual team members. We are resolute in our belief that each team member has an equal responsibility to mold and uphold our culture. 

project44 is an equal opportunity employer seeking to enrich our work environment by creating opportunities for individuals of all backgrounds and experiences to thrive. If you share our values and our passion for helping the way the world moves, we’d love to review your application! 

For any accommodation needed during the hiring process, please email   recruiting@project44.com. Even if you don’t meet 100% of the above job description you should still seriously consider applying. Studies show that you can still be considered for a role if you meet just 50% of the role’s requirements. 

More about project44 

Since 2014, project44 has been transforming the way one of the largest, most important global industries does business. As transportation and logistics continue to evolve and customer expectations around delivery become more demanding, industry technology must rise to the occasion. In just a few short years, we have created a digital infrastructure that eliminates the inefficiencies caused by dated technology and manual processes. Our Advanced Visibility Platform is used by the world’s leading brands to track shipments, collaborate with supply chain partners, drive operational efficiencies, and create outstanding customer experiences. 

About WPP Media 

WPP is the creative transformation company. We use the power of creativity to build better futures for our people, planet, clients and communities. For more information, visit wpp.com. 

WPP Media is WPP’s global media collective. In a world where media is everywhere and in everything, we bring the best platform, people, and partners together to create limitless opportunities for growth. For more information, visit wppmedia.com 

At WPP Media, we believe in the power of our culture and our people. It’s what elevates us to deliver exceptional experiences for both our clients and each other. In this role it will be critical to embrace WPP & WPP Media’s shared core values: 

• Be Extraordinary by Leading Collectively to Inspire transformational Creativity. 
• Create an Open environment by Balancing People and Client Experiences by Cultivating Trust. 
• Lead Optimistically by Championing Growth and Development to Mobilize the Enterprise. 

Role Summary and Impact

As part of the Global Operations Centre (GOC), you will work closely with teams across the United States, Europe, and Asia to deliver high-impact solutions in a collaborative, multicultural environment. We are looking for a Senior Data Engineer, based out of Gurgaon/Bangalore who will:

• Design, develop, and optimize enterprise ETL/ELT pipelines utilizing Azure Data Factory, Azure Data Lake Storage, and advanced serverless technologies—ensuring cross-platform scalability, security, and reliability.
• Implement highly efficient, complex SQL solutions—including advanced query optimization, partitioning, and indexing—to power sophisticated analytics models and enable real-time data processing.
• Lead the development and integration of robust automation frameworks using Python, and API orchestration, introducing innovative solutions to streamline the entire data lifecycle and maximize operational efficiency.
• Exercise full ownership of production pipeline reliability; proactively identify and resolve critical issues through deep root-cause analysis, and institute resilient, long-term stability measures for continuous uptime.
• Establish, refine, and enforce rigorous coding and architectural standards through comprehensive code reviews and technical audits, setting quality benchmarks for the offshore engineering team.
• Champion best-in-class documentation, data lineage, and automated CI/CD deployment practices, ensuring transparency, auditability, and governance across all data assets.
• Demonstrate expert-level support for analytics and media teams, translating business challenges into scalable, high-performance technical solutions, leveraging deep Azure and SQL expertise.

Senior-Level Expectations:

• Act as the organization’s subject matter expert (SME) in end-to-end pipeline architecture, orchestration frameworks, schema evolution, and advanced Azure Data Factory strategies.
• Lead modernization initiatives across the organization, championing the adoption of technologies such as Databricks, DBT and advanced DevOps practices to future-proof the data platform and enable rapid innovation.
• Ensure strict adherence to SLAs and regulatory compliance through advanced monitoring, proactive risk mitigation, and continuous improvement of operational processes.

Skills and Experience:

If this opportunity looks right for you, we are looking for candidates who have:

• 3-4 years of progressive experience in data engineering, with expert-level mastery of Azure Data Factory, SQL, and cloud data platforms (Azure and/or GCP).
• Proven expertise in designing, optimizing, and managing large-scale, production-grade data pipelines, including deep skills in SQL performance tuning, ADF orchestration, and CI/CD automation.
• Advanced knowledge of production operations, troubleshooting, and high-availability data processing at scale.

Good to have-

• Adverity
• Dataflow
• Big Query
• Databricks
• DBT
• Terraform
• Wrike/Jira/Azure DevOps
• DP‑203 / GCP Data Engineer certifications

Life at WPP Media & Benefits 

Our passion for shaping the next era of media includes investing in our employees to help them do their best work, and we’re just as committed to employee growth as we are to responsible media investment. WPP Media employees can tap into the global WPP Media & WPP networks to pursue their passions, grow their networks, and learn at the cutting edge of marketing and advertising. We have a variety of employee resource groups and host frequent in-office events showcasing team wins, sharing thought leadership, and celebrating holidays and milestone events. Our benefits include competitive medical, group retirement plans, vision, and dental insurance, significant paid time off, preferential partner discounts, and employee mental health awareness days.   

WPP Media is an equal opportunity employer and considers applicants for all positions without discrimination or regard to characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.

We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process. 

About WPP Media 

WPP is the creative transformation company. We use the power of creativity to build better futures for our people, planet, clients and communities. For more information, visit wpp.com. 

WPP Media is WPP’s global media collective. In a world where media is everywhere and in everything, we bring the best platform, people, and partners together to create limitless opportunities for growth. For more information, visit wppmedia.com 

At WPP Media, we believe in the power of our culture and our people. It’s what elevates us to deliver exceptional experiences for both our clients and each other. In this role it will be critical to embrace WPP & WPP Media’s shared core values: 

• Be Extraordinary by Leading Collectively to Inspire transformational Creativity. 
• Create an Open environment by Balancing People and Client Experiences by Cultivating Trust. 
• Lead Optimistically by Championing Growth and Development to Mobilize the Enterprise.

Key Responsibilities:

• Design, develop, and optimize enterprise ETL/ELT pipelines utilizing Azure Data Factory, Azure Data Lake Storage, and advanced serverless technologies—ensuring cross-platform scalability, security, and reliability.
• Implement highly efficient, complex SQL solutions—including advanced query optimization, partitioning, and indexing—to power sophisticated analytics models and enable real-time data processing.
• Lead the development and integration of robust automation frameworks using Python, and API orchestration, introducing innovative solutions to streamline the entire data lifecycle and maximize operational efficiency.
• Exercise full ownership of production pipeline reliability; proactively identify and resolve critical issues through deep root-cause analysis, and institute resilient, long-term stability measures for continuous uptime.
• Establish, refine, and enforce rigorous coding and architectural standards through comprehensive code reviews and technical audits, setting quality benchmarks for the offshore engineering team.
• Champion best-in-class documentation, data lineage, and automated CI/CD deployment practices, ensuring transparency, auditability, and governance across all data assets.
• Demonstrate expert-level support for analytics and media teams, translating business challenges into scalable, high-performance technical solutions, leveraging deep Azure and SQL expertise.

Senior-Level Expectations:

• Act as the organization’s subject matter expert (SME) in end-to-end pipeline architecture, orchestration frameworks, schema evolution, and advanced Azure Data Factory strategies.
• Lead modernization initiatives across the organization, championing the adoption of technologies such as Databricks, DBT and advanced DevOps practices to future-proof the data platform and enable rapid innovation.
• Ensure strict adherence to SLAs and regulatory compliance through advanced monitoring, proactive risk mitigation, and continuous improvement of operational processes.

Required Skills:

• 3-4 years of progressive experience in data engineering, with expert-level mastery of Azure Data Factory, SQL, and cloud data platforms (Azure and/or GCP).
• Proven expertise in designing, optimizing, and managing large-scale, production-grade data pipelines, including deep skills in SQL performance tuning, ADF orchestration, and CI/CD automation.
• Advanced knowledge of production operations, troubleshooting, and high-availability data processing at scale.

Life at WPP Media & Benefits 

Our passion for shaping the next era of media includes investing in our employees to help them do their best work, and we’re just as committed to employee growth as we are to responsible media investment. WPP Media employees can tap into the global WPP Media & WPP networks to pursue their passions, grow their networks, and learn at the cutting edge of marketing and advertising. We have a variety of employee resource groups and host frequent in-office events showcasing team wins, sharing thought leadership, and celebrating holidays and milestone events. Our benefits include competitive medical, group retirement plans, vision, and dental insurance, significant paid time off, preferential partner discounts, and employee mental health awareness days.   

WPP Media is an equal opportunity employer and considers applicants for all positions without discrimination or regard to characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.

We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process. 

About WPP Media 

WPP is the creative transformation company. We use the power of creativity to build better futures for our people, planet, clients and communities. For more information, visit wpp.com. 

WPP Media is WPP’s global media collective. In a world where media is everywhere and in everything, we bring the best platform, people, and partners together to create limitless opportunities for growth. For more information, visit wppmedia.com 

At WPP Media, we believe in the power of our culture and our people. It’s what elevates us to deliver exceptional experiences for both our clients and each other. In this role it will be critical to embrace WPP & WPP Media’s shared core values: 

• Be Extraordinary by Leading Collectively to Inspire transformational Creativity. 
• Create an Open environment by Balancing People and Client Experiences by Cultivating Trust. 
• Lead Optimistically by Championing Growth and Development to Mobilize the Enterprise. 

This role will serve as core member of a data engineering team assigned to one of WPP’s major global clients, who will be maintaining and expanding upon a global data warehouse, automated reports, and data provisioning applications to ensure that media and marketing stakeholders the world will have access to the right data and insights to inform their marketing decisions.  

WPP has developed the Measure platform, a stack of standardized technologies (Adverity for collection, DBT for modelling, Google Cloud Platform for orchestration, computing, and storage, and Microsoft PowerBI for visualization) and templates to speed the deployment and simplify support for automated reporting and analytics tools.

The team’s primary responsibility is to build and maintain a global Measure-based reporting solution, leveraging existing templates where applicable and building custom collectors, data models, cloud architectures, and/or visualizations when required. The team will automate the collection and transformation of disparate marketing data into a single source of truth, continually improving it to incorporate new data sources, and to derive new insights, to support ever-evolving business demands.

As an Senior Data Engineer, your primary responsibilities will include deploying and troubleshooting standardized Adverity data collection templates,  QAing landed versus source data using self-developed scripts and manual processes, gathering platform and ad account parameters from upstream stakeholders, working within and contributing to the team building the data warehousing solution,  adhering to technical standards and best practices, and contributing to the documentation of custom work.

In doing so you will exhibit a foundational understanding of cloud technology and key data engineering skills and knowledge to help your team in this fast-evolving and in-demand industry.

Some of the things we’d like you to do:

• Deploy data collectors in Adverity to gather data from media, agency system, and other sources

• Development and maintain data quality checks and procedures, helping stakeholders overcome data issues before they impact the quality of the reporting solution

• Support the translation of user requirements and business needs into technical specifications
• Be a proficient user of Google Cloud Platform and associated technologies, ensuring your work incorporates industry best practice
• Monitor automated jobs, troubleshooting data issues as-and-when they arise
• Support other members of the team responsible for “last mile” transformation and visualization of data within Google Data Studio reports and dashboards
• Serve as a technical and professional leader for junior staff
• Provide hands-on support to users of reporting solutions, helping the wider team triage and respond to user queries in a timely manner
• Attending internal stakeholder meetings, presenting your solutions, and providing updates on your work.
• Support the development strong working relationships with third-party data providers that we rely on for access to necessary data.

A bit about yourself:

Key Responsibilities:

• Design, develop, and optimize enterprise ETL/ELT pipelines utilizing Azure Data Factory, Azure Data Lake Storage, and advanced serverless technologies—ensuring cross-platform scalability, security, and reliability.
• Implement highly efficient, complex SQL solutions—including advanced query optimization, partitioning, and indexing—to power sophisticated analytics models and enable real-time data processing.
• Lead the development and integration of robust automation frameworks using Python, and API orchestration, introducing innovative solutions to streamline the entire data lifecycle and maximize operational efficiency.
• Exercise full ownership of production pipeline reliability; proactively identify and resolve critical issues through deep root-cause analysis, and institute resilient, long-term stability measures for continuous uptime.
• Establish, refine, and enforce rigorous coding and architectural standards through comprehensive code reviews and technical audits, setting quality benchmarks for the offshore engineering team.
• Champion best-in-class documentation, data lineage, and automated CI/CD deployment practices, ensuring transparency, auditability, and governance across all data assets.
• Demonstrate expert-level support for analytics and media teams, translating business challenges into scalable, high-performance technical solutions, leveraging deep Azure and SQL expertise.

Senior-Level Expectations:

• Act as the organization’s subject matter expert (SME) in end-to-end pipeline architecture, orchestration frameworks, schema evolution, and advanced Azure Data Factory strategies.
• Lead modernization initiatives across the organization, championing the adoption of technologies such as Databricks, DBT and advanced DevOps practices to future-proof the data platform and enable rapid innovation.
• Ensure strict adherence to SLAs and regulatory compliance through advanced monitoring, proactive risk mitigation, and continuous improvement of operational processes.

Required Skills

• 3-4 years of progressive experience in data engineering, with expert-level mastery of Azure Data Factory, SQL, and cloud data platforms (Azure and/or GCP).
• Proven expertise in designing, optimizing, and managing large-scale, production-grade data pipelines, including deep skills in SQL performance tuning, ADF orchestration, and CI/CD automation.
• Advanced knowledge of production operations, troubleshooting, and high-availability data processing at scale.

#LI-GOC

Who are we and What do we do?

We help advertisers reach and engage with their target audience globally. We do this through a deep understanding of people, which is enabled through our algorithms that respect privacy. Today, some of the world's largest brands, agencies, developers and publishers are creating great value by using our platforms to deliver compelling proposition to their target consumers.
 Currently, we provide over 1.4 billion mobile users with relevant advertisements that enable meaningful decisions. We display 10 billion advertisements on a daily basis!
 
What’s the InMobi family like?
We are an infectious bunch. Be it the way we rise up to challenges, the cutting edge products we create, the dreams we chase or the fun we have at work. We are sure that if you meet us, you will be infected too. Today, we are proud to be the leaders in Mobile advertising and we are sure to go even higher from here. We invite you to free yourself, dream big and chase your passion. We are here today because a few of us did just that.
 
What can we promise?  
We offer an opportunity to have immediate impact with the company and our products. Modern work environment, flexible schedule and smart, creative, down-to-earth people. Internal opportunities to move roles and try out bridge assignments with different teams.  Food for your soul – free meals all days of the week, gym or Yoga class to flex those biceps, cocktails at drink cart Thursdays and fun at work on Funky Fridays. We even promise to let you bring your kids and pets to work.

What Will You Be Doing?

What Do We Expect From You?

We are growing our data science team and looking for a passionate individual who can bridge the gap between business problems and data solutions.

Key Responsibilities

• Own the end-to-end problem-solving lifecycle: business context → data → AI-driven insights → outcomes
• Work directly with customers and internal teams to understand business problems and define solutions
• Analyze large, complex datasets using SQL and Python
  
• Design and deliver AI-powered analytics solutions using Tellius
• Translate ambiguous business problems into structured analytics or AI workflows
  
• Build and demo insight-driven dashboards and narratives for business users
• Partner closely with Product, Engineering, and GTM teams
  
• Present insights and recommendations confidently to business and technical stakeholders
  

Must-Have Skills

• 3+ years of experience in data science, solutions engineering, or analytics consulting
• Strong hands-on skills in SQL and Python
  
• Experience with cloud data platforms (Snowflake, Databricks, Redshift)
• Hands-on experience with LLMs and AI agents, including prompt engineering, RAG pipelines, AI agent workflows, and deploying AI-driven solutions beyond basic ChatGPT usage.
• Understanding of agentic AI concepts: memory, tool usage, orchestration, multi-step reasoning
• Experience with analytics platforms such as Tableau, Power BI, and ThoughtSpot (you understand what Tellius replaces)
• Domain exposure in pharma commercial analytics, CPG/retail analytics, or FP&A (at least one)
• Strong storytelling, presentation, and stakeholder management skills
• Comfortable in customer-facing roles
  

Good to Have

• Prior experience in an analytics or AI SaaS product company
  
• Exposure to enterprise decision workflows
  
• Experience demoing or solutioning for clients

Who You Are

• Curious, analytical, and business-minded
• Comfortable working in ambiguity
• Excited about AI-native analytics and agentic systems
  
• Strong communicator who can turn insights into action

Why Join Tellius

• Build next-gen, AI-native analytics products
  
• Work on real customer problems with measurable impact
• Collaborate with top talent across AI, data, and product
• Fast growth, high ownership, and strong learning opportunities

What You Will Do and Learn

As a Data Engineer in Data Solutions, you’ll be responsible for designing, implementing, and testing proposed modern analytic solutions.  Working closely with our client partners and architects, you’ll develop relationships with key technical resources while delivering tangible business outcomes. 

Qualifications:

· 2-4 years’ experience developing industry leading business intelligence and analytic solutions

· Must have thorough knowledge of data warehouse concepts and dimensional modelling

· Must have experience in writing advanced SQL

· Must have at least 2+ years of hands-on experience on DBT (Data Build Tool). Mandatory to have most recent hands-on experience on DBT.

· Must have experience working with DBT on one or more of the modern databases like Snowflake / Amazon Redshift / BigQuery / Databricks / etc.

· Hands-on experience with Snowflake would carry higher weightage

· Snowflake SnowPro Core certification would carry higher weightage

· Experience working in AWS, Azure, GCP or similar cloud data platform would be an added advantage

· Hands-on experience on Azure would carry higher weightage

· Must have experience in setting up DBT projects

· Must have experience in understanding / creating / modifying & optimizing YML files within DBT

· Must have experience in implementing and managing data models using DBT, ensuring efficient and scalable data transformations

· Must have experience with various materialization techniques within DBT

· Must have experience in writing & executing DBT Test cases

· Must have experience in setting up DBT environments

· Must have experience in setting up DBT Jobs

· Must have experience with writing DBT Jinja and Macros

· Must have experience in creating DBT Snapshots

· Must have experience in creating & managing incremental models using DBT

· Must have experience with DBT Docs

· Should have a good understanding of DBT Seeds

· Must have experience with DBT Deployment

· Must Experience with architecting data pipelines using DBT, utilizing advanced DBT features

· Proficiency in version control systems and CI/CD

· Must have hands-on experience configuring DBT with one or more version control systems like Azure DevOps / Github / Gitlab / etc.

· Must have experience in PR approval workflow

· Participate in code reviews and best practices for SQL and DBT development

· Experience working with visualization tools such as Tableau, PowerBI, Looker and other similar analytic tools would be an added advantage

· 2+ years of Business Data Analyst experience

· 2+ years of experience writing Business requirements, Use cases and/or user stories, for data warehouse or data mart initiatives.

· Understanding and experience on ETL/ELT is an added advantage

· 2+ years of consulting experience working on project-based delivery using Software Development Life Cycle (SDLC)

· 2+ years of years of experience with relational databases (Postgres, MySQL, SQL Server, Oracle, Teradata etc.)

· 2+ years of experience creating functional test cases and supporting user acceptance testing

· 2+ years of experience in Agile/Kanban/DevOps Delivery

· Outstanding analytical, communication, and interpersonal skills

· Ability to manage projects and teams against planned work

· Responsible for managing the day-to-day client relationship on projects

· Manage the Data engineering lifecycle including research, proof of concepts, architecture, design, development, test, deployment, and maintenance

· Collaborate with team members to design and implement technology that aligns with client business objectives

· Build proof of concepts for a modern analytics stack supporting a variety of Cloud-based Business Systems for potential clients

· Team management experience and ability to manage, mentor and develop talent of assigned junior resources

· Create actionable recommendations based on identified platform, structural and/or logic problems

· Communicate and demonstrate a clear understanding of client business needs, goals, and objectives

· Collaborate with other architects on solution designs and recommendations.