Urwah Admin

Morningstar

<div><div>Location: Mumbai 
Reports to: Tech Team Lead 
 
About the Role 
 
We are looking for a Software Developer/Data Scientist to join our Data Services team, specializing in delivering custom client-ready reports and managing data corrections. This role requires strong technical skills in Python, SQL, and Excel, combined with experience in AWS cloud services such as Athena and Aurora. You will play a key role in ensuring clients receive high-quality, tailored data outputs and that corrections are handled efficiently through automated tools and processes. 
 
Key Responsibilities 
 
<ul><li>Work on Client Platforms with Data Services Core team to Prepare custom Level 3 client reports based on specific requirements and data sets.</li><li>Design, develop, and deploy AI agents capable of performing intelligent data and report functions</li><li>Develop and maintain correction files and tools to manage data adjustments and ensure accuracy.</li><li>Automate repetitive tasks using Python scripts and Excel macros where applicable.</li></ul>
&bull; Perform data validation, quality checks, and ensure compliance with internal standards. &bull; Query and manage data using AWS Athena and Aurora, ensuring scalability and performance. 
<ul><li>Collaborate with Sustainalytics Data Services Digital, Client Services, Business Analysts, Data Engineers teams to deliver timely and accurate outputs.</li><li>Document processes and maintain clear guidelines for report generation and correction workflows.</li><li>Stay up-to-date with the latest developments in AI, and client facing technologies. Required Qualifications</li><li>Bachelor&rsquo;s degree in Computer Engineering, Computer Science, or related field.</li><li>Strong proficiency in Python (data manipulation libraries like Pandas, NumPy).</li><li>Strong knowledge of API integration, and data extraction from both structured and unstructured sources</li><li>Advanced knowledge of SQL for querying and managing relational databases.</li><li>Excellent Excel skills, including formulas, pivot tables, and automation techniques.</li><li>Knowledge of distributed computing and data engineering techniques for scalable data processing</li><li>Hands-on experience with AWS services (Athena, Aurora, S3).</li><li>Strong analytical and problem-solving skills with attention to detail.</li><li>Ability to manage multiple priorities and deliver under tight deadlines. Preferred Skills</li><li>Experience with data visualization tools (Power BI, Tableau).</li><li>Familiarity with version control (Git) and workflow automation.</li><li>Knowledge of financial data and reporting standards is a plus.</li></ul> 
Morningstar is an equal opportunity employer</div>
Morningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.
I10_MstarIndiaPvtLtd Morningstar India Private Ltd. (Delhi) Legal Entity</div>

Senior Software Engineer

<div>At PitchBook, a Morningstar company, we are always looking forward. We continue to innovate, evolve, and invest in ourselves to bring out the best in everyone. We&rsquo;re deeply collaborative and thrive on the excitement, energy, and fun that reverberates throughout the company.
Our extensive learning programs and mentorship opportunities help us create a culture of curiosity that pushes us to always find new solutions and better ways of doing things. The combination of a rapidly evolving industry and our high ambitions means there&rsquo;s going to be some ambiguity along the way, but we excel when we challenge ourselves. We&rsquo;re willing to take risks, fail fast, and do it all over again in the pursuit of excellence.
If you have a good attitude and are willing to roll up your sleeves to get things done, PitchBook is the place for you.
As a member of the Enterprise Data Platform team and Enterprise Technology organization within Technology &amp; Engineering at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.
We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other&rsquo;s words and actions, value constructive discussions and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us!
The Enterprise Data Platform (EDP) team supports rigorous and data-driven decisions with products and services leveraged across PitchBook. Our work produces tools and data to help the enterprise grow and run more efficiently - at both strategic and tactical levels. As our business grows rapidly, our data needs grow to enable employee for success at every level while also enabling enterprise to capitalize on opportunities with speed and confidence.
The Senior Data Product Manager leads the strategy, vision, and development of data products that drive business value and prioritize user-centric principles. In this role, you will be responsible for fostering a culture of accessibility, governance, and data quality while leveraging your expertise in cross-functional collaboration, strategic vision, business acumen, data literacy, and analytical decision-making. This is an exciting opportunity for growth-minded candidates to further their product knowledge and experience in a fast-growing company with unique challenges. This role has excellent potential for career growth further in product management, analytics, and other engineering paths.<h2 class="jobSectionHeader">
Primary Job Responsibilities</h2><ul><li>
Product Strategy &amp; Vision: Develop and execute a strategic roadmap for data products, aligning with company goals. Shape product vision with a focus on data democratization across multiple domains including, PitchBook platform, Marketing, Sales/CS, Product Usage, and more</li><li>
User-Centric Design: Ensure products prioritize end-user needs and experiences. Gather feedback and leverage data insights for user-centric product design</li><li>
Cross-Functional Collaboration: Work closely with revenue operations, engineering, design, data science, and business stakeholders to deliver impactful data products</li><li>
Data Accessibility &amp; Governance: Lead development with a strong focus on accessibility, governance, and ethical data practices</li><li>
Quality Assurance: Implement rigorous processes to maintain data integrity and compliance with quality standards</li><li>
Data Literacy: Translate complex data concepts into actionable strategies for technical and non-technical audiences</li><li>
Innovation &amp; Differentiation: Identify opportunities for innovation that empower PitchBook internal and external customers and drive measurable outcomes</li><li>
Mentorship: Mentor team members, fostering a culture of growth and excellence within the Product organization</li></ul><h2 class="jobSectionHeader">
Skills and Qualifications</h2><ul><li>
Bachelor&rsquo;s degree in Computer Science, Business, Finance, or related field</li><li>
5+ years of product management experience in financial services or data-related roles (data analyst, data scientist, data/software engineering)</li><li>
Demonstrated expertise with public equity datasets (financial statements, industry metrics, SEC filings, etc.) and hands-on experience applying data to deal workflows</li><li>
Strong data literacy and proficiency in data analysis and interpretation</li><li>
Excellent communication and collaboration skills, including with executive-level stakeholders</li><li>
Familiarity with data governance, data quality, and accessibility principles</li><li>
Strategic mindset with a focus on aligning data products with business objectives</li><li>
Experience influencing senior leadership through data-driven insights</li><li>
Proficiency with tools such as Snowflake, SQL, Tableau, modeling platforms, Mixpanel, FullStory</li></ul>
Working Conditions:
The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.
Life At PB:
We are consistently recognized as a Best Place to Work and our culture is at the heart of our success. It&rsquo;s our fundamental belief that people do and create great things and that people are the cornerstone of prosperity. We believe that proactively seeking out different points of view, listening to others, learning, and reflecting on what we&rsquo;ve heard creates a sense of belonging within PitchBook and strengthens the PitchBook community.
Morningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.
037_PitchBookDataInc PitchBook Data, Inc Legal Entity</div>

Sr. Data Product Manager, Enterprise Data Platform

<div>Role: Software Engineer<div>
Location: Vashi, Navi Mumbai 
Reports to: Tech Team Lead 
 
About the Role 
 
We are looking for a Software Developer/Data Scientist to join our Data Services team, specializing in delivering custom client-ready reports and managing data corrections. This role requires strong technical skills in Python, SQL, and Excel, combined with experience in AWS cloud services such as Athena and Aurora. You will play a key role in ensuring clients receive high-quality, tailored data outputs and that corrections are handled efficiently through automated tools and processes. 
 
Key Responsibilities 
 
<ul><li>Work on Client Platforms with Data Services Core team to Prepare custom Level 3 client reports based on specific requirements and data sets.</li><li>Design, develop, and deploy AI agents capable of performing intelligent data and report functions</li><li>Develop and maintain correction files and tools to manage data adjustments and ensure accuracy.</li><li>Automate repetitive tasks using Python scripts and Excel macros where applicable.</li></ul>
&bull; Perform data validation, quality checks, and ensure compliance with internal standards. &bull; Query and manage data using AWS Athena and Aurora, ensuring scalability and performance. 
<ul><li>Collaborate with Sustainalytics Data Services Digital, Client Services, Business Analysts, Data Engineers teams to deliver timely and accurate outputs.</li><li>Document processes and maintain clear guidelines for report generation and correction workflows.</li><li>Stay up-to-date with the latest developments in AI, and client facing technologies.</li></ul></div>
Required Qualifications<ul><li>2 + years of experience</li><li>Bachelor&rsquo;s degree in Computer Engineering, Computer Science, or related field.</li><li>Strong proficiency in Python (data manipulation libraries like Pandas, NumPy).</li><li>Strong knowledge of API integration, and data extraction from both structured and unstructured sources</li><li>Advanced knowledge of SQL for querying and managing relational databases.</li><li>Excellent Excel skills, including formulas, pivot tables, and automation techniques.</li><li>Knowledge of distributed computing and data engineering techniques for scalable data processing</li><li>Hands-on experience with AWS services (Athena, Aurora, S3).</li><li>Strong analytical and problem-solving skills with attention to detail.</li><li>Ability to manage multiple priorities and deliver under tight deadlines. Preferred Skills</li><li>Experience with data visualization tools (Power BI, Tableau).</li><li>Familiarity with version control (Git) and workflow automation.</li><li>Knowledge of financial data and reporting standards is a plus.</li></ul> 
Morningstar is an equal opportunity employer
Morningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.
I10_MstarIndiaPvtLtd Morningstar India Private Ltd. (Delhi) Legal Entity</div>

Software Engineer

<div>Title: Lead Machine Learning Engineer
Location: Vashi, Navi Mumbai
Shift: General
As a Lead Machine Learning Engineer, you will be the hands-on technical owner of ML systems that power large-scale data collection, extraction, enrichment, and understanding of unstructured content. You&rsquo;ll design, build, and operate end-to-end solutions&mdash;from feature generation and training to low-latency inference and observability. These solutions will measurably improve coverage, freshness, quality, and unit cost across our data pipelines. Your toolbox spans classical ML, NLP, LLMs/GenAI, Agentic AI, Retrieval-Augmented Generation (RAG) frameworks, and Model Context Protocol (MCP). You will use these to deliver retrieval, extraction, classification, summarization, and autonomous tasking capabilities integrated cleanly into production workflows.
You&rsquo;ll own the architecture and implementation across AWS and GCP clouds, selecting managed services pragmatically and deploying resilient services via Docker and Kubernetes with CI/CD, autoscaling, canary/shadow releases, and tight SLIs/SLOs. You will institute MLOps best practices&mdash;experiment tracking, model and prompt registries, evaluation harnesses, data/feature drift detection, guardrails and policy enforcement, lineage and access controls&mdash;so teams can ship faster with confidence. Day to day, you&rsquo;ll write production-grade Python and SQL, apply GitHub Copilot to accelerate development responsibly, and partner with Product, Data, Platform/SRE, and Security to translate ambiguous problems into staged, observable deliveries.
You bring a curiosity to understand the domain by studying the applications, dataflow, and data schemas, and you use that context to design simpler, more accurate systems. It&rsquo;s a plus if you have familiarity with public and private equity data and related entity models, enabling smarter features, evaluation sets, and downstream integrations. As a lead IC, you mentor through design and code reviews, set technical direction, and improve reliability, security, and developer experience. You will champion cost-aware, privacy-first designs; lead deep dives to resolve complex issues; and iterate quickly to achieve measurable outcomes (precision/recall, latency, error budgets, and cost per document). This role is ideal for an engineer who thrives on shipping robust ML/LLM systems at scale and influencing cross-functional teams through exceptional technical judgment and execution.
Team Overview
You will be part of a multidisciplinary team of ML engineers and data scientists responsible for building AI &amp; ML solutions and services as part of robust data collection pipelines handling large volumes of unstructured data. Team will focus on building scalable and reliable systems to process and categorize data that is essential for downstream data collection processing.
Outline of Duties and Responsibilities<ul><li>
AI &amp; ML Data Collection Leadership: Convert business goals into a clear AI/ML roadmap for data acquisition, extraction, enrichment, and measurable outcomes.</li><li>
Technical Oversight: Architect and ship scalable ML/NLP/LLM (RAG, embeddings, reranking, Agentic AI, MCP) services with high reliability and efficiency.</li><li>
Peer Leadership &amp; Development: Mentor engineers and data scientists through design/code reviews, setting technical standards and elevating craftsmanship.</li><li>
NLP Technologies: Build and integrate classifiers, transformers, LLMs, and evaluators that process and categorize unstructured data at scale.</li><li>
Data Pipeline Engineering: Design, operate, and optimize high-throughput collection pipelines with robust orchestration, messaging, storage, and SLAs.</li><li>
Cross-functional Collaboration: Partner with Product, Data Collection Engineering, Platform/SRE, and Security to turn ambiguous needs into phased, observable deliveries.</li><li>
Innovation &amp; Continuous Improvement: Pilot and productionize advances in GenAI, Agentic AI, RAG, and MCP to improve quality, speed, and cost.</li><li>
System Integrity &amp; Security: Enforce data governance, privacy, and model transparency with least-privilege IAM, secrets management, and auditability.</li><li>
Process Improvement: Apply Agile/Lean/Fast-Flow practices to reduce cycle time, raise quality, and remove toil via automation.</li><li>
Cloud &amp; Deployment: Deliver cloud-native solutions on AWS and GCP using Docker/Kubernetes, autoscaling, and progressive delivery patterns.</li><li>
MLOps &amp; Reliability: Establish experiment tracking, registries, CI/CD, drift detection, SLIs/SLOs, and runbooks for dependable operations.</li><li>
Retrieval Quality &amp; Evaluation: Implement offline/online evals (e.g., nDCG/MRR/precision@k), golden sets, and guardrails for RAG and search relevance.</li><li>
Cost, Performance &amp; Observability: Optimize latency and unit cost with caching, batching, distillation, right-sizing, and clear dashboards/alerts.</li><li>
Documentation &amp; Knowledge Sharing: Produce concise design docs, ADRs, and playbooks to ensure durable, cross-site knowledge transfer.</li></ul>
Experience, Skills and Qualifications<ul><li>
Bachelor&rsquo;s, Master&rsquo;s, or PhD in Computer Science, Mathematics, Data Science, or a related field.</li><li>
8+ years of experience in the ML Engineering and Data Science field, with a focus on LLM and GenAI technologies, particularly in data collection and unstructured data processing.</li><li>
3+ years of experience in technical lead position.</li><li>
Strong expertise in NLP and machine learning, with hands-on experience in classifiers, large language models (LLMs), Model Context Protocol (MCP), Agentic AI, and other advanced NLP techniques.</li><li>
Extensive experience with data pipeline and messaging technologies such as Apache Kafka, Airflow, and cloud data platforms (e.g., Snowflake).</li><li>
Expert-level proficiency in Python, SQL, and other relevant programming languages and tools.</li><li>
Proficiency in Amazon Web Services (AWS) and Google Cloud Platform (GCP).</li><li>
Strong understanding of cloud-native technologies and containerization (e.g., Kubernetes, Docker) with experience in managing these systems globally.</li><li>
Demonstrated ability to solve complex technical challenges and deliver scalable solutions.</li><li>
Excellent communication skills with a collaborative approach to working with global teams and stakeholders.</li><li>
Experience working in fast-paced environments, particularly in industries that rely on data-intensive technologies (experience in fintech is highly desirable).</li></ul>
Working Conditions
The job conditions for this position are in a standard office setting. Employees in this position use PC and phones on an ongoing basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.
Morningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.
I10_MstarIndiaPvtLtd Morningstar India Private Ltd. (Delhi) Legal Entity</div>

Lead Machine Learning Engineer

Join Morningstar and explore 4   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Morningstar

ABOUT_COMPANY

Senior Software Engineer

Sr. Data Product Manager, Enterprise Data Platform

Software Engineer

Lead Machine Learning Engineer