Data Instrumentation And Growth Measurement Lead Jobs

WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. Why we're hiring: We are seeking an experienced and detail‑oriented Global Data Steward to join our team in Chennai, India, supporting WPP Media’s global Master Data Management (MDM) initiative. This role plays a critical part in maintaining the integrity of WPP Media’s Golden Master Data assets across domains such as Clients, Media, Suppliers, and other core business entities. The role works hands‑on with AI‑assisted mastering and mapping in our internally developed MDM platform, Matrix. The role requires strong ownership, sound judgement, and an attitude focused on getting it right — not just getting it approved. The Global Data Steward is expected to actively drive data quality outcomes, challenge poor inputs or AI recommendations, and ensure that master data decisions are correct, intentional, and fit for long‑term enterprise use. As a Global Data Steward, you will work cross‑region with markets, finance teams, and global stakeholders. A structured, proactive, and assertive (“pushy when needed”) approach is essential to ensure mappings are completed, standards are met, and nothing critical stalls.

About PayPay India PayPay, a fintech company providing a service enjoyed by over 75 million users since its launch in 2018 in Japan. The company is now home to a very diverse team of members from more than 50 countries. We grew to a team of several thousand employees in Japan but are far from over. We are still in the Day 1. Every day, new members join us from all over the world to create new value and deliver it to society. Why India ? To build our Payment services, we got technical cooperation from Paytm (A large payment service company in India). And based on their customer-first technologies , we created and expanded the smartphone payment service in Japan. Therefore, we have decided to establish a development base in India, because it is a major IT country with many talented engineers, as evidenced by the fact that cutting-edge mobile payments can continue to be generated. OUR VISION IS UNLIMITED We dare to believe that we do not need a clear vision to create a future beyond our imagination. PayPay will always stay true to our roots and realise a vision (future) that no one else can imagine by constantly taking risks and challenging ourselves. With this mindset, you will be presented with new and exciting opportunities on a daily basis and have the opportunity to grow and reach new dimensions that you could never have imagined. Job Description PayPay India is looking for a Data Engineer to work on our payment system to deliver the best payment experience for our customers. This platform is vital to support our increasing business demands. The Data Pipeline team is tasked with creating, deploying, and managing this platform, utilizing leading technologies like Databricks, Delta Lake, Spark, PySpark, Scala, and the AWS suite. We are actively seeking skilled Data Engineers to join our team and contribute to scaling our platform across the organization. Main Responsibilities Create and manage robust data

Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,400 firms in nearly 60 countries use Addepar to manage and advise on nearly $9 trillion in assets. Its open platform integrates with nearly 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, London, Edinburgh, Pune, Dubai, Geneva, Singapore and São Paulo. The Role Part of the broader Addepar Data Management organisation, the Portfolio Data Operations team is responsible for ensuring Addepar's clients have timely and high quality data. This will include overseeing the processing of transactions and positions so that it meets client timelines, ensuring data quality through verification checks, and helping clients with their data support questions. The Portfolio Data Operations team sits at the nexus of Addepar's activity and requires daily communications with data providers, clients, and other personnel within Data Operations and across the firm. Applicants must have legal authorization to work in the country where this role is based on the first day of employment. Visa sponsorship is not available for this position. What You’ll Do Perform daily internal verification checks to ensure portfolio account data is accurate and available within SLAs Investigate and troubleshoot data pipeline issues and data feed processing exceptions, and triage with Engineering Support when needed Complete and maintain operational workflows, and identify and implement opportunities for optimisation Collaborate with Client Support, Solution Architects, and other members of Sales and Services to address client data inqu

Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,400 firms in nearly 60 countries use Addepar to manage and advise on nearly $9 trillion in assets. Its open platform integrates with nearly 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, London, Edinburgh, Pune, Dubai, Geneva, Singapore and São Paulo. The Role We are currently seeking a Portfolio Data Analyst to join our Portfolio Data Feeds Team! Addepar provides asset owners and advisors a clearer financial picture at every level, allowing them to make more informed and timely investment decisions. As a Portfolio Data Analyst focusing on our portfolio data platform, you will be responsible for integrating client portfolio data into Addepar’s leading portfolio management products. You will work closely with data providers, internal partners and engineering to expand Addepar’s capabilities and coverage to meet client needs. You will partner closely with leaders across the business to build the preeminent data solutions and services that serve investment teams in wealth management and beyond. In addition, you work with other partners within the product management team on a variety of initiatives to improve overall data management and integration across Addepar. Applicants must have legal authorization to work in the country where this role is based on the first day of employment. Visa sponsorship is not available for this position. What You’ll Do Analyse and onboard portfolio data content from a variety of sources using industry standard analysis tools (such as SQL and Jupyter Notebooks) int

A CAREER WITH POINT72’S DATA SOURCING TEAM: We are looking for a Market Data Operations Associate to join our Enterprise Data Sourcing Team to help manage day-to-day market data operations around data governance, entitlement management, and market data support. In this role, you will support our expanding data requirements and strategic business initiatives around firmwide market data. What you’ll do: Manage and monitor market data and service change notifications from exchanges and other key market data suppliers Identify any gaps in market data usage and coverage and provide proper licensing recommendations Administer and manage market data entitlements for market data feeds (e.g. TREP, BPIPE) and terminals (e.g. Bloomberg Terminals, FactSet Workstation, CapIQ) Help manage exchange audits to fulfil their requirements, including working with usage statistics via SERS / DACS / EMRS reports Help ensure the firm’s market data access and usage is compliant with licensing agreements Help manage the full lifecycle of market data exchange contracts and renewals, including tracking of user inventory and key commercial terms Help provide additional ad-hoc administrative support around the firm’s market data operations, including invoice reconciliation, internal reporting, etc. What’s required: Bachelor’s or Master’s degree in finance, economics, computer science, business, or related field (with a strong academic record). 4+ years of experience in market data management within a financial services or trading environment. Strong understanding of exchange data licensing, entitlements, and governance policies. Familiarity with market data platforms, feed technologies, and integration processes. Knowledge of global trading markets and regulatory requirements. Strong problem-solving skills with the ability to anticipate issues and propose solutions. Detail-oriented with the ability to track policy changes and ensure operational compliance. Proj

JOB TITLE Reference Data Engineer A Career with point72’s Cubist TEAM Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. What you’ll do Develop, test, and maintain software applications using .NET Full Stack technologies. Write clean, scalable, and efficient code in Python for various applications. Collaborate with cross-functional teams to define, design, and ship new features. Implement and manage CI/CD pipelines and other DevOps practices to ensure smooth deployment and operation of software solutions. Participate in code reviews and contribute to a culture of continuous improvement. Troubleshoot and resolve software defects and issues in a timely manner. Stay up to date with emerging technologies and industry trends to enhance skills and knowledge. What’s REQUIRED We are looking for a motivated and skilled Software Engineer with experience in .NET Full Stack development, Python, and DevOps. You should also have: Bachelor’s or master’s degree in computer science, engineering, statistics or a related field. 3+ years of experience in .NET Full Stack development and Python programming. Basic understanding and practical experience with DevOps tools and methodologies. Strong problem-solving skills and attention to detail. Excellent communication skills and the ability to work collaboratively in a team environment. Eagerness to learn and adapt to new technologies and challenges. Commitment to the highest ethical standards. About point72 Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its inves

ROLE We are passionate about data. We collaborate to build elegant, effective, scalable and highly reliable solutions to empower predictive modelling in finance. Cubist’s Data Services (CDS) group is looking for a Data Scientist to join our dedicated data team. Our group is responsible for the timely delivery of comprehensive and error-free data to some of the most demanding and successful systematic Portfolio Managers in the world. As a Data Scientist in the team, this individual will play a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure, and the live production trading of billions of dollars of capital across global capital markets, including equities, futures, options and other financial instruments. RESPONSIBILITIES Onboarding novel datasets from a huge variety of sources into our platform Develop, test and deploy data pipelines, applications and services Re-shaping, aggregating, enhancing and creating features from datasets Engaging with vendors and internal stakeholders to understand characteristics of datasets Defining and automating qualitative data alerts and reports Partnering closely with investment teams to ensure their data requirements are met Perform preliminary analysis and research to be shared with investment teams REQUIREMENTS Masters in Financial Engineering, Statistics, Computer Science or other disciplines involving rigorous quantitative analysis Strong programming skills in Python and SQL Experience working with AWS, Linux and Airflow preferred but not required Financial industry experience preferred but not required Strong organization, communication and interpersonal skills Attention to detail and a love of processes Strong oral and written communication skills Ability to exercise sound judgment in assessing and determining how to handle queries, calls and issues Ability to multitask and prioritize assignments Commitment to the highest ethica

Opportunity Overview We're hiring a Data Architect who will serve as a senior technical leader responsible for architecting the complete lifecycle data moves, transforms, and creates value across every product line we operate. You'll own the blueprint for our enterprise data lakehouse - setting the standards, governance, and strategy that elevate data from a byproduct of operations to the company's most valuable asset. We need someone who pairs deep mathematical and logical modeling expertise with a builder's instinct - someone who codes, prototypes fast, and proves out next-generation AI data architectures before committing the organization to them. This role would need experience with US healthcare domain data. What You'll Do Semantic Layer Governance: Set the technical standard and reference architecture for a universal semantic layer across multiple distinct data products, ensuring unified definitions of complex metrics and healthcare business entities across Architect the Enterprise Context Layer: Define, scale, and govern the global Enterprise Ontology (abstract domain maps, business entity classes, and entity-relationship rules) that serves as the backbone for Agentic AI systems. AI-Native Prototyping : Leverage modern AI-native development environments (such as Cursor, GitHub Copilot) to rapidly generate, iterate, and document blueprints for complex enterprise data schemas and metadata layers. Security & Compliance Leadership : Embed regulatory compliance (HIPAA, FHIR) and security principles into platform design. Partner with security and compliance teams to ensure architectural decisions support audit readiness and risk mitigation. Cross-Functional Collaboration : Partner with executive leadership, product management, and engineering to translate business requirements into scalable technical solutions. Communicate complex architectural concepts to both technical and non-technical stakeholders. ISMS roles and responsibilities Good knowledge of Informati

Opportunity Overview: We are seeking a Senior Data Engineer to contribute to the design and delivery of our cloud-native healthcare data platform. You will implement scalable data solutions built on AWS, Apache Iceberg, Lake Formation, Glue Catalog, Athena, dbt, and modern orchestration frameworks. This role combines strong hands-on engineering with collaboration across platform, analytics, and business teams. What You'll Do Data Engineering Delivery Deliver complex data engineering projects in collaboration with cross-functional teams Drive technical execution from design through production deployment Implement scalable data patterns and reusable frameworks Design and implement batch and near-real-time pipelines Build reusable ingestion, transformation, validation, and publishing frameworks Support modernization of legacy workloads Contribute to Apache Iceberg implementation and optimization Apply standards for schema evolution, partitioning, compaction, and metadata management Ensure efficient storage and query performance Implement data quality frameworks and validation layers Support observability and monitoring practices Contribute to operational excellence and reliability improvements Participate in architecture and design discussions Conduct and participate in code reviews Mentor junior engineers and share best practices ISMS roles and responsibilities Good knowledge of Information security Oversee specific business processes within the ISMS. Responsible to manage the ISMS documentation, conduct risk assessments, and implement risk treatment plans. Risk Owners are responsible for identifying, assessing, and managing risks within their areas of responsibility. They are also responsible for implementing risk treatment plans. Conduct the BCP and other test related to information security continuity along with CISO Responsible for monitoring and reporting on the performance of the ISMS. Responsible for implementation of security policies and procedures and report

Opportunity Overview: As a Staff Data Scientist at Cohere Health, you will serve as a technical leader across high-priority initiatives, shaping how data science is applied to some of the most complex challenges in healthcare. You’ll drive the design of advanced analytical and modeling solutions, influence strategic direction, and partner deeply across Product, Clinical, and Engineering to deliver scalable, high-impact outcomes. This role goes beyond execution. You’ll define approaches, set standards, and guide others in solving ambiguous, high-leverage problems. You’ll play a critical role in advancing the maturity of data science at Cohere while contributing directly to improving clinical and operational decision-making. What you’ll do: Lead the design and execution of complex, high-impact data science initiatives across multiple domains Define analytical frameworks and modeling approaches for ambiguous, strategic problem spaces Partner with senior stakeholders to shape problem definition, prioritize opportunities, and influence decision-making Develop and deploy advanced models and scalable analytical solutions that drive measurable outcomes Establish best practices for experimentation, model development, and analytical rigor across the team Mentor and guide other data scientists, providing technical leadership and elevating team capabilities Drive cross-functional alignment to ensure solutions are practical, scalable, and integrated into workflows ISMS roles and responsibilities: Good knowledge of Information security Oversee specific business processes within the ISMS. Responsible to manage the ISMS documentation, conduct risk assessments, and implement risk treatment plans. Risk Owners are responsible for identifying, assessing, and managing risks within their areas of responsibility. They are also responsible for implementing risk treatment plans. Conduct the BCP and other test related to information security continuity along with CISO Responsible for monitor

Opportunity Overview: We are seeking a Lead Data Engineer to drive the design and delivery of our cloud-native healthcare data platform. You will lead the implementation of scalable data solutions built on AWS, Apache Iceberg, Lake Formation, Glue Catalog, Athena, dbt, and modern orchestration frameworks. This role combines deep hands-on engineering with technical leadership and collaboration across platform, analytics, and business teams. What you’ll do: Lead Data Engineering Initiatives Lead delivery of complex data engineering projects across multiple teams Drive technical execution from design through production deployment Establish scalable implementation patterns Build and Optimize Data Platforms Design and implement batch and near-real-time pipelines Build reusable ingestion, transformation, validation, and publishing frameworks Support modernization of legacy workloads Lakehouse Engineering Lead Apache Iceberg implementation and optimization Define standards for schema evolution, partitioning, compaction, and metadata management Ensure efficient storage and query performance Data Quality and Reliability Implement data quality frameworks Drive observability and monitoring practices Improve operational excellence and reliability Technical Leadership Review architecture and design proposals Conduct code reviews and engineering reviews Mentor engineers and establish best practices ISMS roles and responsibilities: Good knowledge of Information practices. Assist the manager in all the information security activities implementation and maintenance process. Ensuring the team and imparted with Competence related to Information security Responsible for implementation of security policies and procedures and report any issues to the Information Security Manager. Required Qualifications: 8–12 years of Data Engineering experience. Experience leading enterprise-scale data initia

About the Team Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. By implementing pipelines, data structures, and data warehouse architectures; this team serves as the foundation for decision-making at DoorDash. About the Role DoorDash is looking for a Softare Engineer II to be a technical powerhouse to help us scale our data infrastructure, automation and tools to meet growing business needs. You're excited about this opportunity because you will… Work with business partners and stakeholders to understand data requirements Work with engineering, product teams and 3rd parties to collect required data Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse Develop and implement data quality checks, conduct QA and implement monitoring routines Improve the reliability and scalability of our ETL processes Manage a portfolio of data products that deliver high-quality, trustworthy data Help onboard and support other engineers as they join the team We're excited about you because… 3+ years of professional experience working in data engineering, business intelligence, or a similar role You have proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software Proficiency in programming languages such as Python/Java 3+ years of experience in ETL orchestration and workflow management tools like Airflow, Flink, Oozie and Azkaban using AWS/GCP Expert in Database fundamentals, SQL and distributed computing 3+ years of experience with the Distributed data/similar ecosystem (Spark, Hive, Druid, Presto) and streaming technologies such as Kafka/Flink. Experience working with Snowflake, Redshift, PostgreSQL and/or other DBMS

At FourKites we have the opportunity to tackle complex challenges with real-world impacts. Whether it's medical supplies from Cardinal Health or groceries for Walmart, the FourKites platform helps customers operate global supply chains that are efficient, agile and sustainable. Join a team of curious problem solvers that celebrates differences, leads with empathy and values inclusivity. As a Senior Data Scientist, you will build and own machine learning models that power core prediction problems across the FourKites platform — including ETA/ATA forecasting and message-based status extraction. You will work end-to-end, from data pipeline to production deployment and monitoring, turning noisy real-world logistics data into models that run at scale and directly move the needle on customer outcomes. You will work closely with product, engineering, and operations teams, hands-on building and shipping models yourself while also guiding the technical direction of other data scientists on the team. What you'll be doing: Design, build, and productionize ML models for problems like ETA/ATA prediction, using regression, classification, and time-series forecasting techniques Develop NLP/LLM-based extraction pipelines for message-based ETA and status updates (text extraction, entity recognition) Own models end-to-end: data pipeline → training → deployment → monitoring → retraining Work with noisy, real-world logistics and supply chain data (GPS pings, check calls, carrier data) rather than clean, pre-processed datasets Diagnose gaps between offline evaluation performance and live production accuracy, and drive fixes Build and maintain automated training/retraining pipelines using orchestration tools such as Airflow Set up and maintain model monitoring and observability (e.g., Grafana) to catch drift and degradation proactively Replace manual or rule-based processes with ML-driven automation (e.g., automating manual check calls) Translate model performance improvements into busin

About the Team DoorDash is a data driven organization and relies on timely, accurate and reliable data to drive many business and product decisions. The Core Data Platform organization owns all the infrastructure necessary to run an operationally efficient analytical data stack. About the Roles The Data Platform team spans data mobility frameworks, ingestion, infrastructure, tools, and governance. Together, they design and operate scalable compute and ingestion frameworks using technologies such as Spark, Flink, Kafka, Airflow, and modern lakehouse solutions, while also building abstractions and tools that simplify data workflows for engineers, analysts, and ML practitioners. In parallel, these teams establish strong data quality, cataloging, privacy, and compliance standards to ensure trust in analytics and regulatory adherence. As relatively high-impact teams, they offer engineers the opportunity to shape the roadmap, influence core platform decisions, and directly enable DoorDash’s business-critical insights and real-time personalization capabilities. You must be located in San Francisco, CA, Sunnyvale, CA, Seattle, WA, or New York, NY. You're excited about this opportunity because you will… Drive vision & strategy for building the frameworks charter and position it to handle the challenges of a rapidly growing business. Scale the analytical platform for the increasing amounts of data and use cases. You will bring your expertise in building and operating high scale systems with a focus on reliability, scalability and cost efficiency. Collaborate with stakeholders building solutions on top of the platform Foster a positive and supportive work culture, upleveling others. We're excited about you because you have… B.S., M.S., or PhD. in Computer Science or equivalent. 2+ years of industry experience at our I4 level, 5+ years of industry experience at our I5 level Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in th

Opportunity Overview: We are seeking a Technical, Hands-on Manager to lead a team responsible for building and maintaining high-quality healthcare market datasets and analytics that power internal insights, benchmarking, and external thought leadership . In this role, you will lead a team of data analysts responsible for the development, quality assurance, and ongoing refresh of market data assets. You will combine strong people leadership with technical expertise in analytics and data science to ensure reliable, scalable data pipelines and actionable insights. The ideal candidate is both a strong people manager and a hands-on analytics leader who can guide analysts in rigorous data methodology, translate data outputs into meaningful business insights, and partner closely with commercial strategy, product, clinical, and analytics stakeholders. What you’ll do: Lead and develop a team of data analysts responsible for the creation, validation, and ongoing refresh of healthcare market datasets. Mentor analysts in data methodology, statistical reasoning, and reproducible analytics practices to ensure consistent and rigorous analysis across the team. Establish analytic standards, coding practices, and documentation expectations to ensure all datasets and insights produced by the team are reproducible and scalable. Establish and maintain governance processes for market data including versioning, documentation, auditability, and traceability of data sources and methodologies. Oversee change-detection logic, ensuring the team systematically identifies and documents additions, removals, and shifts in the market dataset. Define and enforce data quality standards across ingestion, transformation, and analysis workflows. Collaborate with Data Engineering and Platform teams to ensure the underlying data infrastructure supports scalable ingestion, transformation, and analytics workflows used by the analyst team. Translate analytic outputs into business insights, benchmarks, and st