The I&O Platform Infrastructure Data Analyst collects, processes and analyzes operational data from EY's infrastructure platforms to provide actionable insights and support continuous improvement of the Hyperconverged Service Platform.
Compensation
We offer a competitive remuneration package where you'll be rewarded for your individual and team performance.
Responsibilities
Collect, process and analyze operational data from infrastructure platforms
Transform raw data into insights and visualizations
Own KPI reporting for HCSP
Partner with engineering and leadership teams to drive data-informed culture
Provide hands-on expertise in designing, delivering and supporting reliable, secure, scalable and cost-conscious data solutions across COFCO International as a senior/specialist contributor within the Data Engineering team.
Responsibilities
Deliver assigned engineering and support work
Translate business and data requirements into technical designs, development estimates and delivery plans
Design, develop and maintain end-to-end ETL/ELT pipelines and data models across enterprise data-lake and other business data solutions
Guide Azure Data Factory and Azure Synapse delivery, including SQL, Spark-based transformations, notebooks and pipeline orchestration
Deliver integrations between source systems, data platforms and downstream consumers
Requirements
Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems or a related discipline
A Data Analyst is responsible for gathering, analyzing and problem solving as it relates to data, types of data, and relationships among data elements within a business system or IT system and with business domain expertise.
Responsibilities
Analyze data to extract meaningful insights, trends, and patterns that can support decision-making across the organization.
Develop and maintain dashboards and visualizations using Power BI, Spotfire, and Tableau to present data insights in an easy-to-understand format for stakeholders.
Work with Azure Synapse Analytics, Azure Data Lake, and Azure SQL Database to store, transform, and retrieve data efficiently.
Assist in data preparation, cleaning, and integration activities for analysis, ensuring high data quality.
Collaborate with data engineers, business stakeholders, and IT teams to understand data requirements and contribute to the delivery of data-driven solutions.
Requirements
Bachelor's degree in Data Analytics
Bachelor's degree in Computer Science
Bachelor's degree in Statistics
Nice to have: Microsoft Power BI Data Analyst certification (PL-300)
Nice to have: Cloud Certifications in Microsoft Azure
The Data Transformation Specialist will help build, scale, and maintain MPI’s business intelligence and data science platform, improving data quality and streamlining data feeds processes.
Responsibilities
Contributes to data pipelines by implementing a solid, robust, extensible design that supports key business flows.
Performs data transformations to populate data-hub, data-lake, data warehouse, reporting databases and downstream data marts.
Identifies technical requirements and delivers solutions by establishing efficient design and programming patterns that meet Service Level Agreements (SLAs) and help manage the data platform.
Responsible for finding trends in data sets and developing algorithms to help make raw data more useful to the enterprise.
Designs, integrates, and documents technical components for seamless data extraction and analysis.
Requirements
Degree in Computer Science, Information Technology, or related technical discipline
As an Analytics Engineer you will sit at the intersection of data engineering and business intelligence - modelling, transforming, and publishing clean, tested, and reusable datasets that power dashboards, predictive models, and KPI frameworks across the organisation.
Locations (3)
European Union
Latin America
Ukraine
Compensation
A competitive salary and good compensation package
Responsibilities
Design and build data products across the full data lifecycle - from ingestion through transformation to serving.
Develop robust, well-documented data models in close collaboration with business users, data engineers, and analytics architects.
Extract, transform, and validate data from diverse sources including JSON & XML feeds, leveraging strong metadata management practices.
Design and deliver AI-powered capabilities using large language models (LLMs), with a focus on effective context management, reliability, and measurable customer value. Build retrieval-augmented generation (RAG) solutions using technologies such as Azure Cosmos DB and semantic search to provide relevant, grounded responses. Apply AI-assisted and agentic development practices and tools to improve engineering productivity, quality, and delivery.
Responsibilities
Design and deliver AI-powered capabilities using large language models (LLMs), with a focus on effective context management, reliability, and measurable customer value.
Build retrieval-augmented generation (RAG) solutions using technologies such as Azure Cosmos DB and semantic search to provide relevant, grounded responses.
Apply AI-assisted and agentic development practices and tools to improve engineering productivity, quality, and delivery.
Requirements
Bachelor's Degree in Computer Science or related technical field
Master's Degree in Computer Science or related technical field
Design and deliver AI-powered capabilities using large language models (LLMs), with a focus on effective context management, reliability, and measurable customer value. Build retrieval-augmented generation (RAG) solutions using technologies such as Azure Cosmos DB and semantic search to provide relevant, grounded responses. Apply AI-assisted and agentic development practices and tools to improve engineering productivity, quality, and delivery.
Responsibilities
Design and deliver AI-powered capabilities using large language models (LLMs), with a focus on effective context management, reliability, and measurable customer value.
Build retrieval-augmented generation (RAG) solutions using technologies such as Azure Cosmos DB and semantic search to provide relevant, grounded responses.
Apply AI-assisted and agentic development practices and tools to improve engineering productivity, quality, and delivery.
Requirements
Bachelor's Degree in Computer Science or related technical field
Master's Degree in Computer Science or related technical field
Nice to have: large language models (LLMs)
Nice to have: context management
Nice to have: retrieval-augmented generation (RAG)
Design, build, test, and deploy automated data pipelines and ETL/ELT processes on Azure and Databricks platform, develop data models, and oversee vendor deliverables.
Locations (2)
Hyderabad, Telangana, India
Warsaw, Masovian Voivodeship, Poland
Compensation
Competitive starting salary and benefits program (private health care, P&G stock, saving plans, sport cards).
Responsibilities
Design, build, test, and deploy automated data pipelines and ETL/ELT processes on Azure and Databricks
Write clean, maintainable, production-ready code in Python and PySpark
Develop, tune, and optimize complex SQL queries
Ensure end-to-end data quality, consistency and reliability
Act as technical point of contact and quality gatekeeper for vendor deliverables
Design, develop, and maintain scalable data pipelines and Big Data solutions on Microsoft Azure and related platforms.
Responsibilities
Design, develop, and maintain scalable data pipelines using PySpark, Spark SQL, Python, SQL, and Azure Synapse Analytics.
Build and optimize ETL/ELT workflows for large-volume structured, semi-structured, and unstructured data processing.
Develop and support Azure Synapse pipelines, notebooks, SQL scripts, stored procedures, views, and data transformation logic.
Work with Azure Data Lake Storage Gen2, Azure Data Factory, Azure Databricks, Azure SQL Database, and related Azure data services.
Develop and support Big Data solutions using technologies such as Apache Spark, Hadoop, HDFS, Hive, Sqoop, Kafka, HBase, and related distributed data processing components.
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