Role Description - Partner with the Head of Practice, and contribute to the shaping of the Data Management (DM) strategy of customers and ensuring all activities and tasks undertaken are linked to the overall strategy and priorities of the practice. - Senior and lead development of the solutions around Data management platforms comprising of various modern capabilities satisfying the needs of both data provisioning and consumption persona in the data ecosystem: e.g. capabilities that simplify, streamline, automate processes like data ingestion, transformation, orchestration, discovery, MDM, data quality, data cataloging, exploration, governance, etc. - Drive experimentation and POCs with tools and explore building of accelerator solutions which are aligned with the DM strategy, and which can quickly be deployed to the benefit of requesting customers. - Collaborate with other team members and clients as required to build the solution landscape. - Lead consulting engagements related to Data Quality & Observability metadata management and data cataloging. - Drive innovation leveraging emerging capabilities in technology landscape: AI/ML, GenAI, Automation, and leading Data & Cloud Platforms. - Coaching junior members of the team including extended teams. Qualifications - 10+ years of experience in building data architecture and software solutions for organizations. - Strong command over backend solution architecture and data engineering using tools such as Databricks, Spark, Microsoft Fabric, Snowflake, BigQuery, AWS Glue, and NoSQL DBs. - Proven experience of using agentic development tools such as Cursor, Claude Code, Github Copilot or similar to boost work productivity. - Experience implementing self-serve, metadata driven data pipelines. - Expertise in cloud platforms such as Azure, and GCP preferred. - Experience highly desirable – 3 or more of the following: - Implementation of data lakes, data lakehouse, data mesh or data fabric. - Certification or experience with any Data catalog, or MDM SaaS solution. - Certification or experience with any Data Quality or Data Observability solution. - Data modeling, Advanced SQL. - DEVOps/SecOps pipelines and CI/CD implementations. - Developing and testing web-application with React or Angular Frontend, Rest or graph API’s. - Experience with LangChain, LangGraph, LangSmith or similar Agentic frameworks. - Very good Programming skills in Python, Java, or other languages to deliver a wide variety of data services. - Basic understanding or exposure to traditional analytics: reporting / BI is preferred. - Practical knowledge of modern capabilities in AI and agentic frameworks and emerging use cases in the data management ecosystem preferred. Requirements - Timeliness and quality of Deliverables: building offerings, proposals, leading assessments, POCs. - Balances creativity with planned and structured execution aligned with organizational strategy and priorities. Seeks clarity, stays focused, and prioritizes deliverables. - Ensures proposal of solutions aligned with customer data strategy and requirements. - Liaises with sales and delivery teams as required. - Demonstrate learning agility to learn and implement new AI and Data concepts and solutions. - Outside-in perspective, and generation/adoption/implementation of innovative ideas. - Strong customer orientation. - Ensures clear communication of risks, issues, and expectations. - Capability of building robust solution architecture involving assembly and integration of various tools. - Passion for automation and hands-on with technical deliverables. Other Qualifications - Bachelors in engineering, mathematics, or statistics. - FMCG/ CPG industry experience is highly desirable.

Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. What this opportunity involves While each project involves unique tasks, contributors may: - Design rigorous statistics problems reflecting professional practice; - Evaluate AI solutions for correctness, assumptions, and constraints; - Validate calculations or simulations using Python (NumPy, Pandas, SciPy, Statsmodels, and Scikit-learn); - Improve AI reasoning to align with industry-standard logic; - Apply structured scoring criteria to multi-step problems. What we look for This opportunity is a good fit for statisticians with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  - Degree in Statistics or related fields, e.g. Probability Theory, Mathematical Statistics, Applied Statistics, etc. - 3+ years of professional mathematics experience - Strong written English (C1/C2) - Strong Python proficiency for numerical validation - Stable internet connection  Professional certifications (e.g., PStat, CAP, SAS Certifications) and experience in international or applied projects are an advantage. How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Compensation On this project, contributors can earn up to $73 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. What this opportunity involves While each project involves unique tasks, contributors may: - Design rigorous statistics problems reflecting professional practice; - Evaluate AI solutions for correctness, assumptions, and constraints; - Validate calculations or simulations using Python (NumPy, Pandas, SciPy, Statsmodels, and Scikit-learn); - Improve AI reasoning to align with industry-standard logic; - Apply structured scoring criteria to multi-step problems. What we look for This opportunity is a good fit for statisticians with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  - Degree in Statistics or related fields, e.g. Probability Theory, Mathematical Statistics, Applied Statistics, etc. - 3+ years of professional mathematics experience - Strong written English (C1/C2) - Strong Python proficiency for numerical validation - Stable internet connection  Professional certifications (e.g., PStat, CAP, SAS Certifications) and experience in international or applied projects are an advantage. How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Compensation On this project, contributors can earn up to $73 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. What this opportunity involves While each project involves unique tasks, contributors may: - Design rigorous statistics problems reflecting professional practice; - Evaluate AI solutions for correctness, assumptions, and constraints; - Validate calculations or simulations using Python (NumPy, Pandas, SciPy, Statsmodels, and Scikit-learn); - Improve AI reasoning to align with industry-standard logic; - Apply structured scoring criteria to multi-step problems. What we look for This opportunity is a good fit for statisticians with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  - Degree in Statistics or related fields, e.g. Probability Theory, Mathematical Statistics, Applied Statistics, etc. - 3+ years of professional mathematics experience - Strong written English (C1/C2) - Strong Python proficiency for numerical validation - Stable internet connection  Professional certifications (e.g., PStat, CAP, SAS Certifications) and experience in international or applied projects are an advantage. How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Compensation On this project, contributors can earn up to $73 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.