... more product deployments of big data technologies – Business Data Lake, NoSQL databases etc - Awareness and decision-making ability to choose among various big data, NoSQL, analytics tools and technologies - Should have experience in architecting and implementing domain centric big data solutions - At MakeMyTrip, we're committed ...
... (dashboard creation, data modeling, DAX/Calculated Fields). - Solid understanding of SQL for data extraction and manipulation. - Experience working with relational databases (e.g., MySQL, PostgreSQL, BigQuery). - Strong understanding of data visualization best practices and storytelling with data. - Experience in cleaning, transforming, ...
... Design, develop, and maintain scalable data pipelines and ETL processes leveraging AWS services such as S3, Glue, EMR, Lambda, and Redshift.- Collaborate with data scientists and analysts to understand data requirements and implement solutions that support analytics and machine learning initiatives.- Optimize data storage ...
... not a backend analytics role — this is a core product + innovation role . Key Responsibilities 1. Data Strategy & Architecture Design and implement end-to-end data systems for healthcare and wellness products Identify key data points across user behavior, health patterns, and outcomes Build scalable data pipelines and infrastructure ...
... clients and each other. Create an Open environment by Balancing People and Client Experiences by Cultivating Trust. Deploy data collectors in Adverity to gather data from media, agency system, and other sources ~ Development and maintain data quality checks and procedures, helping stakeholders overcome data issues before they ...
Key Responsibilities: Design and implement ELT processes for diverse data sources, including RDBMS, NoSQL databases, and data warehouses Develop and maintain scalable data pipelines for batch and stream processing using JVM-based languages and frameworks Collaborate with cross-functional teams to integrate diverse data ...
... including DORA metrics (lead time, deployment frequency, MTTR, change-failure rate), code coverage, cyclomatic complexity targets, and P99 latency standards.- Data Governance & Enterprise Security: Drive the strategy and implementation for enterprise data governance, metadata management, data lineage, and strict GCP security ...
As a Data Centre Provisioning Engineer, you will be responsible for supporting the deployment, activation, and operational excellence of hyperscale data centre network infrastructure. You will collaborate with cross-functional teams and external partners to ensure seamless provisioning, troubleshooting, and optimization ...
As a lead data scientist in the EDO, Collection Platforms & AI - Cognitive Engineering team, you will own the technical direction of a large-scale entity resolution and linking This platform combines classical ML and GenAI techniques to power intelligent matching and linking services across multiple data domains, exposed ...
... Solutions Architect - Data Engineering based in India. This is a senior, client-facing opportunity for a technical leader who can transform complex business and data challenges into scalable, production-ready solutions. You will lead architecture and delivery across modern Data & AI platforms while partnering directly with ...
... conception to delivery in Data & Analytics area Good understanding of data modelling and building clean, scalable pipelines. Experience with ETL tools and integrating data from multiple sources. Strong knowledge of data management, data warehousing, and big data technologies. Proficiency in data analytics tools and programming languages ...
... Department: Engineering Model Data & Experience As a Senior Data Analyst, you will play a key role in the EMT initiatives, helping transform how engineering data is interpreted and used across the entire value chain. You will work on analyzing trends, clarifying data definitions, identifying inconsistencies, and ensuring ...
... techniques, and perform data mining using state-of-the-art methods. Extend the company's data infrastructure with third-party sources of information and enhance data collection procedures to include all data relevant for building robust analytic systems. Data Quality Assurance: Analysis & Automation: Perform ad-hoc analysis, ...
... workflows for real-world use cases. Mindrift is looking for highly skilled Senior Python Data Scraping Engineers to join the Tendem project and drive specialized data scraping workflows for real-world applications. In this role, you'll apply your expertise in web scraping, data extraction, and data processing to deliver accurate, ...
... develop, and maintain scalable data pipelines using Python and Apache Spark.- Implement efficient ETL/ELT processes for large-scale structured and unstructured datasets.- Develop and optimize complex SQL queries, data models, and transformations.- Ensure data quality, integrity, and reliability across the https://jobeax.com/link/KGEJVg5sFMkW48k2 ...
... https://jobeax.com/link/34bhrmqrKNaUPIfW Description :As a Member of the Data & Analytics team, youll work on transforming data from multiple sources into useful, consistent and easily consumable data elements. Youll strive to continuously improve the data lake and data warehouse and achieve our goals of a best-in-class data https://jobeax.com/link/APpiNK4veXFqKSBZ ...
Working with data collected from market research surveys to provide a variety of output reports, using software products such as Quantum, SPSS, Dimensions Processing, formatting and presenting the data in accordance with global NIQ quality standards Prioritize, structure and deliver data processing (data table production, ...
... part of our expert team, you'll have the opportunity to ensure operational excellence that makes a real difference in organizational performance. As a Clinical Data Team Lead, you will act as the lead data manager for one or more projects or provide support to the lead data manager. You may lead all data management activities ...
... analysis including but not limited to data analysis to extract actionable insights, exploring datasets to uncover patterns and anomalies, analyzing historical data for trend identification and forecasting, investigating data discrepancies, providing user training and support on data analysis tools, communicating findings ...