Data Conversion Project Manager (Pune)

About Forma.ai: Forma.ai is a Series B startup that's revolutionizing how sales compensation is designed, managed and optimized. We handle billions in annual managed commissions for market leaders like Edmentum, Stryker, and Autodesk. Our growth has been fuelled by our passion for fundamentally changing and shaping how companies use sales intelligence to drive business strategy. We’re welcoming equally driven individuals who are excited about creating something big! About the team: The Customer Operations team is at the heart of Forma.ai's mission. This team has a direct impact on the growth of Forma.ai. They are results-driven and solutions-minded. The Customer Operations team works closely with our customers, helping them to understand and take advantage of all the features Forma.ai offers and ensuring that they get the most value from the platform. What you'll be doing: Reporting & Dashboarding Design, maintain, and enhance dashboards in BI tools (e.g., Looker Studio, Salesforce/HubSpot reports) to monitor marketing campaign performance, sales pipeline health, lead flow, and conversion metrics Automate recurring reports and implement self-serve analytics capabilities for GTM teams Data Analysis & Insights Analyze funnel performance from top-of-funnel marketing campaigns to bottom-of-funnel sales outcomes Provide regular insights into key KPI s like campaign ROI, customer acquisition cost (CAC), and attribution across channels Support A/B testing initiatives, sales activity analysis, and segmentation strategies Scripting & Automation Write Python and SQL scripts to extract, clean, and structure data from external sources (e.g., job boards, press releases, M&A feeds, web scraping APIs ) Build automated enrichment pipelines to augment CRM and marketing data with third-party insights (e.g., firmographics, hiring activity, technology stack, fun

Key Responsibilities Enterprise Data Strategy & Client Engagement: Develop and maintain a comprehensive data architecture strategy that aligns with organizational and client business objectives. Serve as a key technical advisor for clients, translating business requirements into innovative data solutions. Build and maintain strong client relationships by providing expert guidance and managing expectations throughout project lifecycles. Data Modeling, Design & Engineering: Design and optimize both logical and physical data models to support enterprise-wide systems. Architect data warehousing solutions, overseeing the integration of data from multiple sources to enable robust business intelligence and analytics. Directly develop, test, and implement ETL processes and data pipelines, ensuring data quality, consistency, and performance. Technology Evaluation & Implementation: Evaluate emerging data technologies and tools to determine their fit within the existing architecture and potential for future scalability. Oversee the integration of new technologies into the enterprise data architecture, balancing innovation with risk management. Team Leadership & Hands-On Management: Lead cross-functional teams, providing mentorship and technical guidance to junior data engineers and architects. Maintain a hands-on approach by actively participating in coding, design sessions, and troubleshooting complex data issues. Ensure project milestones are met through effective resource management and team coordination. Performance, Security & Best Practices: Optimize data storage, retrieval, and processing performance across various systems. Collaborate with security teams to enforce data governance, compliance, and privacy standards. Establish and promote best practices in data management, data engineering, and architecture design. Documentation & Reporting: Develop and maintain comprehensive documentation covering data architecture designs, data flows, integrati

Overview: We are looking for a Senior Data Engineer with deep expertise in Lakehouse architecture, real-time data streaming, cloud data infrastructure, and microservices development on Azure Kubernetes Service (AKS). You will play a central role in designing and delivering next-generation data pipelines, BI solutions, AI/ML platforms, streaming APIs, and scalable microservices that power Guidepoint's research and analytics products. This is a high-impact, hands-on engineering role. You will work closely with data architects, data scientists, analysts, frontend engineers, QA, and DevOps teams to translate complex business requirements into scalable, reliable, and observable data systems. This is a Hybrid role from our Pune office. What You'll Do: Data Engineering & Lakehouse Design, build, and maintain ETL pipelines, data ingestion workflows, and table schemas on Azure Databricks to support BI, analytics, and AI/ML use cases Architect and optimize the Lakehouse using Delta Lake on Databricks, ensuring reliability, performance, and cost efficiency Build and support data pipelines from business applications such as Salesforce, NetSuite, and other enterprise systems Develop and maintain Knowledge Graph models, entity relationship structures, and NLP-based insight pipelines Maintain data governance, data privacy standards, and compliance best practices throughout the data lifecycle Perform root cause analysis on data and processes to identify opportunities for improvement Collaborate with data architects, scientists, and business consumers to populate and optimize the data warehouse for reporting and analytics Microservices & AKS Development Develop and support scalable web APIs and microservices using Python and Azure Platform Services Build new applications, services, and platforms; optimize existing solutions and refactor legacy components using modern, scalable architec

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 As part of the broader Addepar Data Management & Quality organization, the Data Client Support team is responsible for ensuring our customers receive first-class support experience and are able get the most value out of their data in Addepar. The Data Client Support team sits at the nexus of Addepar's activity and requires daily communications with clients, data providers, and other personnel across the company. Important : This role requires for you to be in office 3 days per week in Pune. 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 Address client inquiries related to Addepar’s portfolio data feeds and on general data product functionalities within established SLAs. Manage and complete requests from internal Data teams that require client outreach and/or action to resolve data verification issues. Investigate client reported bugs and data processing issues, and triage with Engineering & Product when needed. Partner with Account Managers, Solutions Architects, and other members of GTM to drive alignment on data related escalations and ensure positive outcomes for clients.

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 As a Data Solutions Consultant, you will support some of Addepar’s complex and high-touch client data implementation projects. You’ll design scalable solutions to transform and integrate clients’ portfolio data into Addepar, and build expertise across both technical and business domains. You’ll also be among the first members of the Data Solutions team based in India , helping establish our presence in the region while working closely with colleagues across the U.S., U.K., and other global offices. This is a collaborative role offering the opportunity to shape our operating model locally and strengthen how our global teams deliver together. Beyond client delivery, you’ll also have the opportunity to participate in internal innovation; contributing to automation, tooling, and best practices that enable scale and elevate how we operate globally. This is an individual contributor position for someone who thrives at the intersection of finance, data, and technology, and is excited to make a global impact from India. 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 Support compl

Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth. The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner… What you will be doing? As a Data Engineer, your role involves crafting and maintaining robust data pipelines, utilising Python and SQL, to ensure efficient extraction, transformation, and loading (ETL) of data. Your responsibilities will include: Data Pipeline Development: Building and optimising data pipelines to facilitate seamless data flow across systems and platforms. Database Management: Managing databases, ensuring their integrity, and implementing data storage and retrieval solutions. Cloud Services Integration: Leveraging cloud services such as MS Azure, GCP, and AWS to architect and deploy scalable data solutions. Machine Learning Integration: Collaborating with teams to integrate machine learning models into data pipelines for enhanced data processing. Utilising Spark & Kafka: Implementing and working with Spark and Kafka for real-time data processing and analytics. What we are looking for? Proficiency in Python, SQL, and database management. Experience with Data Pipelines ETL, Cloud Services ( MS Azure, GCP preferred) , ML Modeling, Spark & Kafka. Proven problem-solving skills and a solution-oriented mindset. Excellent communication skills to collaborate effectively within teams and with stakeholders. Strong business acumen with an interest in business-facing roles. Adaptability and a start-up mentality to thrive in a dynamic environment. Candidates with similar skill sets and experiences have excelled in technology firms or consultancy firms. Successful ca