Top Data Scientist Jobs in Delhi
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As an Analytics Engineer at Kong, responsible for data engineering and product analytics tasks, optimizing the data ecosystem, collaborating with cross-functional teams, and deriving actionable insights. Key responsibilities include data engineering, product analytics, data quality and governance, collaboration, and utilizing the Kong data ecosystem.
Design and implement data solutions using various technical stacks and programming languages. Provide thought leadership and recommend technologies and solutions. Develop custom data pipelines and optimize SQL queries. Must have at least 4 years of experience as a Software Engineer, Data Engineer, or Data Analyst.
Seeking a Senior Data Engineer to design and implement data solutions, develop data pipelines, optimize data models, and collaborate with teams for seamless integration and visualization. Mentor junior team members and stay updated with industry best practices.
Seeking a Senior Staff Data Engineer to lead the development of data infrastructure, data processing, and quality checks. Responsibilities include setting strategic vision, providing technical leadership, collaborating with data scientists, and optimizing data infrastructure for performance and scalability.
Design, build, and shape data pipelines and infrastructure to support a modern data lake for a clinical trial enrollment platform. Work directly with sponsors and external parties on data products. Support internal and external data products by building, scaling, and integrating data processes. Ensure compliance with regulatory frameworks and drive best practices for high-performance systems.
Seeking a Senior Data Engineer to design, model, and implement data analysis solutions, support ETL pipeline modules, and work on large-scale data analytics platforms. Must have strong analytical skills, be a self-motivated learner, and have excellent communication skills. Experience with Java, JavaScript, Apache Spark, and data analysis is required.
Design and implement the full Data Science life-cycle, optimize ETL processes, build predictive models, define and implement data-driven solutions, and influence product decisions with data. Requires strong experience in data analysis, SQL, and e-commerce dashboards.
As a Data Engineer at Demyst, you will be responsible for collaborating with internal project managers, sales directors, and clients to build external data-driven solutions using Python, Pandas, ETL, APIs, SQL, Git, and more. The role involves analyzing data, designing code blocks, and maintaining production solutions.
Responsible for analyzing and visualizing data, building ETL pipelines, and creating reports for stakeholders. Must have strong skills in SQL, Python, and Tableau.
Orion Innovation is seeking a Data Engineer with 7 to 10 years of experience in data engineering, focusing on Microsoft technologies. The role involves expertise in Azure data services, data modeling, and strong communication skills.
Design and develop quantitative models using statistical analysis, mathematical modeling, and programming languages like Python, R, or MATLAB. Analyze large datasets to extract meaningful insights, identify trends, correlations, and patterns relevant to the development of quantitative models. Implement and validate statistical techniques, machine learning algorithms, and financial models to support decision-making processes. Validate models by comparing outputs against historical data and market observations, ensuring accuracy and reliability. Document model methodologies, validation procedures, and results comprehensively to comply with regulatory requirements and facilitate knowledge sharing. Assess and mitigate risks associated with quantitative models, ensuring models adhere to risk management policies and guidelines.
Participate in large-scale client engagements, analyze business requirements, lead data migration, develop ETL processes, provide post-load analysis and data fixes, ensure compliance with data protection legislation, work in an inclusive environment at NAVISITE - Part of Accenture.
Participates as a senior member of data development team, completes data analysis, and develops batch, real-time, and streaming data integration codes independently. Designs, prepares, and automates test cases, applies technical knowledge to maintain data engineering, and implements complex infrastructure and software solutions using company and open-source technologies.
Senior Data Engineer responsible for providing high-quality data sets, building data products, developing data models, and maintaining data pipelines. Collaborates with various teams and ensures data solutions meet SLAs. Requires expertise in Big Data technologies, SQL optimization, ETL processes, AWS ecosystem, and programming languages like Python, Java, and Scala.
Drivetrain is looking for a Data Engineer to build and monitor large-scale data pipelines, develop DBT setup, collaborate with the data platform team, and craft cutting-edge data solutions.
Seeking a Senior Analytics Engineer to lead the transformation layer of a data platform at a fast-growing fintech company. Responsibilities include developing scalable patterns, ensuring data discoverability, and collaborating with various teams. Must have 3+ years of experience in data engineering or analytics, expertise in SQL and Python, and strong relational database skills.
Seeking an enthusiastic Entry-Level Data Engineer with a focus on AI to assist in designing, building, and maintaining data infrastructure that supports artificial intelligence and machine learning initiatives. Responsibilities include data pipeline development, data integration, AI & ML support, data monitoring, and troubleshooting. Preferred skills include practical knowledge of programming languages, SQL, AI frameworks, big data technologies, cloud platforms, data modeling, and strong analytical skills.
Seeking bright and resourceful individuals for the Data team at AlphaGrep, a quantitative trading and investment firm in Mumbai. Responsibilities include building infrastructure tools, optimizing data delivery, coordinating with global teams, and writing efficient code. Required skills include Python and SQL knowledge. Good to have experience with web crawling, Linux environment, and stock market data.
As a Data Engineer at Walmart, you will be responsible for developing and maintaining data pipelines to support data science initiatives. You will work with a mammoth scale of data to create valuable data assets for retail analytics. Collaboration with Data Scientists, Analysts, and business stakeholders to solve complex challenges is crucial for evolving the retail business model.
The Data Engineer Associate at Genworth works closely with Project Stakeholders and Technical team to develop and maintain Pre/Post processing programs and ML models. Responsibilities include building machine learning pipelines, developing python programs, utilizing GCP tools, working with cross-functional teams, and developing Enterprise API and Microservices using Python, JavaScript, Docker, Kubernetes.
Join Thrasio as a Senior Data Analytics Engineer to solve complex business problems by leveraging data, building scalable processes, and compelling visualization. Partner with stakeholders, develop scalable data solutions, and drive efficiency in processes.
Design, build, and maintain scalable data pipelines and ETL processes, collaborate with teams, optimize database systems, implement data quality processes, evaluate new tools and technologies, troubleshoot data-related issues, document processes, stay current with industry trends, guide and mentor team members, stakeholder management, and leadership skills.
The Data Engineer II is responsible for ensuring accurate and pertinent data for the Legal and Compliance departments. They extract and analyze data from multiple databases/platforms, design analytics models, and address business challenges. The role involves ensuring data integrity, conducting root-cause analyses, and implementing corrective measures for data-related issues.
Collaborate with stakeholders to understand data requirements and develop data models. Design data integration processes and data warehousing solutions. Establish data governance policies and procedures. Work with cross-functional teams and stay informed about data modelling trends.
The Data Practise Lead will be responsible for designing technical solutions, data architecture, and data security for U.S, Europe, and APAC clients. They will work on data models, databases, ETL workflows, data integration, and data quality within the organisation. Additional responsibilities include collaborating with stakeholders, staying current with industry trends, and implementing data quality tools.
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