Bigquery Jobs in Mumbai

About Us At Quantiphi, technology is the foundation of our business, but our true strength lies in our global and diverse culture. We take pride in fostering an environment built on transparency, diversity, integrity, continuous learning, and growth. If you re looking for a workplace that encourages innovation and supports your growth both professionally and personally Quantiphi is the perfect fit for you. Role & Responsibilities As a Looker Developer, you will play a key role in building and maintaining data models, developing impactful visualizations, and ensuring optimal performance of our Looker platform. You will collaborate with stakeholders to transform complex data into actionable insights, empowering teams to make data-driven decisions. Key Responsibilities: Create and maintain LookML code to define data models, dimensions, measures, and relationships within Looker. Develop reusable LookML components to streamline and standardize dashboard creation. Design and customize dashboards with effective data visualizations (charts, graphs, etc.) to present insights clearly. Write complex SQL queries to extract and manipulate data as needed, optimizing for performance. Identify and resolve performance bottlenecks impacting report and dashboard loading times. Optimize Looker performance through query tuning, caching strategies, and exploring indexing options. Configure user roles and permissions to manage access and enforce data security best practices (including row-level and field-level security). Leverage Looker APIs, SDKs, and the extension framework where necessary to build custom solutions. Use version control tools like Git to manage LookML code changes and collaborate with development teams. Provide training and support to business users, enabling them to effectively leverage Looker for their analysis needs. Troubleshoot and resolve technical issues related to data models, reports, and dashboards. Skills & Experience Required Hands-on experience with LookML and a strong understanding of Looker s data modeling framework. Strong SQL skills with the ability to write and optimize queries across different SQL dialects (preferably GCP/BigQuery). Knowledge of data modeling best practices and practical experience in building efficient data models. Proficiency in ETL processes for data transformation and preparation. Ability to design visually compelling and user-friendly dashboards within Looker. Performance tuning expertise, including query optimization, caching strategies, and indexing. Familiarity with related tools such as BigQuery, Apache Spark, and Python for data transformations. Strong analytical and problem-solving capabilities. Knowledge of data governance principles to ensure data quality, privacy, and compliance. Excellent understanding of advanced Looker features such as liquid variables, complex derived tables, caching, and PDTs (Persistent Derived Tables). Strong troubleshooting skills to identify root causes and effectively resolve issues related to data modeling, queries, and dashboards. Willingness to stay updated with the latest features and advancements in Looker and data analytics. Nice to Have Experience creating end-to-end documentation for data models, processes, and reports. Familiarity with cloud platforms (GCP, AWS, or Azure) and their data ecosystems. Exposure to advanced scripting for automation and monitoring within the BI environment. If you re excited about working in a fast-paced, collaborative environment with a team of enthusiastic over-achievers, Quantiphi is the place to be!

Job Title: Data Collection Transformation Senior Associate Location: Mumbai Experience: Relevant experience in data acquisition, ESG data management, process automation, and data quality. Company: MSCI About MSCI: MSCI is a global leader in decision-support tools and services for the investment community. With over 50 years of expertise in research, data, and technology, we help clients understand key drivers of risk and return, enabling them to build more effective portfolios with enhanced transparency. At MSCI, we foster a culture of innovation, high performance, and inclusion, empowering our people to grow their careers through continuous learning and a wide range of internal mobility opportunities. Your Team: The ESG Data Collection team plays a critical role in acquiring, validating, and maintaining high-quality ESG data that powers MSCI s ESG products. As part of this team, you will work at the forefront of MSCI s ESG transformation agenda, driving projects that enhance data quality, scalability, and automation to meet the evolving ESG landscape and its growing importance in global financial markets. Your Key Responsibilities: Collaborate with internal ESG Research and Technology teams to design and operationalize data collection processes aligned with evolving ESG and Climate frameworks. Work on electronification of ESG policies and principles by converting them into structured, operational data definitions. Develop data collection templates and translate them into implementable data models. Conduct hands-on research and analysis of company disclosures to support scalable data collection solutions. Analyze collected and third-party datasets to detect patterns and trends, enabling development of automated anomaly detection frameworks. Design and implement contextual/thematic QA checks to strengthen data quality controls, leveraging historical data correction patterns. Collaborate with technology teams to build NLP-driven data extraction models (leveraging both traditional methods and LLMs) to automate identification and extraction of relevant ESG facts from disclosures. Help establish and optimize new data collection processes while ensuring seamless integration with existing workflows. Deliver high-quality data aligned with MSCI methodology, service-level agreements, and regulatory requirements. Contribute to creating methodology and SOP documentation, embedding data and content expertise into internal processes. Drive process automation by developing tools and systems for automated data quality diagnostics, reducing manual intervention. Build dashboards and reports to visualize data quality metrics, identify outliers, and provide data-driven recommendations to stakeholders. Partner with internal stakeholders, including downstream teams, Research, and Product teams, to understand data requirements and ensure seamless delivery. What We re Looking For: Strong analytical mindset with a keen attention to detail. Hands-on experience with Python/SQL for data analysis and process automation; exposure to Machine Learning/RPA is a plus. Experience working with visualization tools such as Power BI. Advanced Excel skills, with the ability to manipulate and analyze complex datasets. Self-starter with strong problem-solving abilities, capable of working in unstructured environments. Strong collaboration and communication skills, with comfort working across hierarchies, functions, and geographies. Previous experience in Financial Services, Technology, or Business Analysis, ideally with exposure to ESG data. Basic understanding of financial markets and asset classes; ESG knowledge would be a significant advantage. Preferred Qualifications: Bachelor s or Master s degree in Finance, Economics, Environmental Science, Data Science, Business, or a related field. Certifications in ESG, Sustainable Finance, or Data Analytics are a plus. What We Offer: Transparent compensation and comprehensive benefits tailored to your location. Flexible work options and access to cutting-edge technology. A culture of learning and development, with access to LinkedIn Learning Pro and Learning@MSCI. Clear career progression paths with opportunities for internal mobility and leadership development. A global network of talented colleagues, supported by inclusive Employee Resource Groups like Women in Tech, Climate Action Network, and more. Qualification : Bachelors or Masters degree in Finance, Economics, Environmental Science, Data Science, Business, or a related field.

about the role Data Engineer identifies the business problem and translates these to data services and engineering outcomes. You will deliver data solutions that empower better decision making and flexibility of your solution that scales to respond to broader business questions. key responsibilities As a Data Engineer, you are a full-stack data engineer that loves solving business problems. You work with business leads, analysts and data scientists to understand the business domain and engage with fellow engineers to build data products that empower better decision making. You are passionate about data quality of our business metrics and flexibility of your solution that scales to respond to broader business questions. If you love to solve problems using your skills, then come join the Team Searce. We have a casual and fun office environment that actively steers clear of rigid "corporate" culture, focuses on productivity and creativity, and allows you to be part of a world-class team while still being yourself. Consistently strive to acquire new skills on Cloud, DevOps, Big Data, AI and ML Understand the business problem and translate these to data services and engineering outcomes Explore new technologies and learn new techniques to solve business problems creatively Think big! and drive the strategy for better data quality for the customers Collaborate with many teams - engineering and business, to build better data products preferred qualifications Over 1-2 years of experience with Hands-on experience of any one programming language (Python, Java, Scala) Understanding of SQL is must Big data (Hadoop, Hive, Yarn, Sqoop) MPP platforms (Spark, Pig, Presto) Data-pipeline & schedular tool (Ozzie, Airflow, Nifi) Streaming engines (Kafka, Storm, Spark Streaming) Any Relational database or DW experience Any ETL tool experience Hands-on experience in pipeline design, ETL and application development Good communication skills Experience in working independently and strong analytical skills Dependable and good team player Desire to learn and work with new technologies Automation in your blood

Deputy Vice President Data Science Location: Mumbai Function: Technology Digital and Data Sciences Employment Type: Full Time Role Overview We are seeking a seasoned and innovative Deputy Vice President Data Science to lead cutting-edge AI and data science initiatives. The ideal candidate will drive the development and deployment of machine learning models, architect cloud-native AI platforms, and guide strategic transformation through advanced analytics. This role requires strong leadership, deep technical expertise, and the ability to collaborate across business and technology teams to deliver measurable impact. Key Responsibilities AI & Machine Learning: Design, develop, and implement advanced machine learning models for predictive analytics, NLP, computer vision, and recommendation engines. Lead end-to-end AI project lifecycles, including model validation, productionization, and continuous optimization using frameworks like TensorFlow, PyTorch, and scikit-learn. Stay current with the latest developments in Generative AI, foundation models, and LLMs; evaluate and integrate them into solutions where applicable. Identify and prioritize AI use cases in collaboration with cross-functional teams to create business value. Data Science & Analytics: Lead the complete analytics lifecycle from data exploration and model building to insight generation and product deployment. Work closely with data engineers and analysts to develop scalable, high-impact solutions that influence business outcomes. Leadership & Strategy: Mentor and develop junior team members, promoting a culture of learning, experimentation, and excellence. Contribute to enterprise-wide AI and cloud strategies, including vision setting and roadmap development. Cloud Architecture & Engineering: Architect and implement cloud-native AI and data platforms on GCP (preferred), with working knowledge of AWS or Azure. Build and optimize scalable ML workflows and data pipelines using platforms like Vertex AI, SageMaker, or Azure ML. Ensure secure, scalable, and cost-effective infrastructure, supported by CI/CD pipelines and MLOps best practices. Required Skills & Qualifications Technical Proficiency: Strong coding skills in Python and SQL. Expert-level knowledge of ML frameworks: TensorFlow, PyTorch, Hugging Face, scikit-learn. Practical experience with Large Language Models (LLMs), vector databases, and Retrieval-Augmented Generation (RAG) techniques. Cloud & Engineering: Proficient in designing solutions on Google Cloud Platform (GCP); experience with AWS or Azure is a plus. Familiarity with data tools like BigQuery, Kafka, Snowflake. Strong knowledge of MLOps, including CI/CD pipelines, model monitoring, and A/B testing frameworks. Governance & Ethics: Solid understanding of data privacy, governance, and responsible AI principles.