... teams to integrate predictive models into live production environments, ensuring low-latency performance and high reliability.- Conduct deep-dive exploratory data analysis on large-scale financial datasets to uncover hidden patterns that drive product strategy and business growth.- Partner with stakeholders to define key ...
... - Solid understanding of data pipeline fundamentals, including ingestion, transformation, and loading (ETL/ELT) processes. - Must have experience with batch data processing (scheduling, dependencies, failure recovery, performance tuning). - Knowledge of data warehousing concepts and familiarity with relational databases. ...
Requirements Strong programming skills in Python and SQL. Experience with data processing leveraging programming skills in Python and Spark. In-depth understanding of the Kafka platform for (real-time) data ingestion and processing of high-volume data. Design and architect data flows and data management in a Cloud environment ...
... Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader. Work with data and analytics experts to strive ...
... Java, JavaScript, or Python OR equivalent experience. Experience building scalable and highly available cloud services spanning multiple regions and/or clouds. Data modeling and big data processing experience Experience in work management and asset inventory systems #This position will be open for a minimum of 5 days, with ...
... governance principles, data quality checks on each data layer. - A successful history of manipulating, processing and extracting value from large disconnected datasets. - Working knowledge of message queuing, stream processing, and highly scalable big data data stores. - Strong project management and organizational skills. ...
... and mitigate data risks throughout the data lifecycle, including protection, retention, storage, use, and quality l Partner with technology teams to capture data sources, formats, and data flows so that data can be validated for downstream analytics and reporting l Investigate and document potential data quality issues, ...
... vector-based data pipelines for AI and GenAI use cases Develop scalable batch and streaming data pipelines using cloud-based data platforms (e.g., Snowflake or Databricks) Create and evolve semantic data models that transform raw data into analytics-ready, trustworthy datasets Build data preprocessing, validation, and quality-assurance ...
... knowledge and troubleshooting capabilities. Database backup and recovery. Database performance tuning and optimization. High availability and disaster recovery. Database security and access management. Database monitoring and capacity management. Database patching and upgrades. Data migration and database maintenance. Infrastructure ...
... partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Senior Data Analyst Product Data & Analytics Team Senior Data Analyst – Product Data & Analytics Product Data & Analytics team builds internal analytic partnerships, strengthening ...
... stakeholders. Data Engineering Data Warehousing Data Modelling ETL / ELT Development Data Integration Data Quality Management Data Reconciliation Data Governance Data Lineage & Metadata Management Oracle Database Advanced SQL / PLSQL SAP BODS Oracle Data Integrator (ODI) Python Unix / Linux Performance Tuning Data Analysis ...
... ownership, OR - 2-3 years as Data/Backend Engineer with PM work (PRDs, roadmaps, user research) Technical Stack Depth Deep understanding: ETL/ELT pipelines, data warehousing, data lakes/lakehouses Advanced SQL (query optimization, not just SELECT statements) Hands-on with ONE of: Hive/Spark/Hadoop/HDFS, Snowflake/Databricks/BigQuery, ...
... 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 ...
... architectures like RNNs and LSTM , BERT Should have worked with cognitive services from major cloud platforms like AWS and have a working knowledge of SQL and no-SQL databases. Ability to create data and ML pipelines for more efficient and repeatable data science projects using MLOps principles Keep abreast with new tools, algorithms ...
... factual accuracy, or comparing responses — when projects are available. While each project involves unique tasks, contributors may: - Carefully review provided data (text, images, or videos); - Label or classify content based on project guidelines; - Identify and flag factually incorrect, sensitive, inappropriate, or unclear ...
... required for optimal extraction, transformation, and loading of data from various sources using SQL and AWS 'big data' technologies. Create and maintain optimal data pipeline architecture. Identify, design, and implement internal process improvements, automating manual processes, optimizing data delivery, re-designing infrastructure ...
... first destination for organisations seeking growth. With our guidance, our clients can make bold, strategic decisions with confidence. Overview of the role In Data Science we work with the data from fast changing consumer goods world. Data comes both from standardized databases and from online retail channels in various ...
... shape. Senior Data Scientist We have an opportunity for a Senior Data Scientist to join our Data Science team in Bangalore, reporting to the Senior Director, Data Science. In this pivotal role, you will drive advanced analytics and machine learning solutions that power our security, networking, and cloud data products. ...
... self-service data exploration capabilities for users to analyze and visualize data independently. Develop reporting and analysis applications to generate insights from data for business stakeholders. Design and implement data models to organize and structure data for analytical purposes. Implement data security and federation strategies ...