Description and Requirements GG10.2 Data Engineer plays a critical role in data and analytics life cycle and significantly contributes to production grade data and analytics solutions. The role requires one to demonstrate Big Data, Engineering and Cloud expertise.It is an individual contributor role, expected to independently function 5-8+ years of relevant experience Bachelors degree in computer science, information technology or equivalent educational qualification • Design, build, and maintain robust ETL/ELT pipelines on cloud(Azure) or on-prem to collect, ingest and store large volumes of structured and unstructured data for batch/real time processing• Monitor, optimize, and troubleshoot data pipelines to ensure reliability, scalability, and performance• Ensure data processing, quality, security, and compliance guidelines, policies and standards are followed• Collaborate with multiple partners from Business, Technology, Operations and D&A capabilities (Data Governance, Data Quality, Data Modeling, Data Architecture, Data science, DevOps, BI & insights) • SQL, Python/Scala• NoSql and distributed databases (Hbase, Cosmos DB)• ETL pipleine development• Big Data Frameworks : Apache Spark, Hadoop, Hive• Cloud platforms: Azure data factory, Eventhub, Azure functions, Synapse, Databricks• Datawarehouses, data marts, data lakes• Medallion architecture• Performance tuning, optimization, and data quality validation• Real-time and batch data processing , streaming pieplines with Spark• Communication skills, analytical skills, structured problem-solving skills.,• Partner, Stakeholder engagement experience • DevOps practices: Git, AzureDevops, CI/CD pipelines• Unix shell scripting, MongoDB, Nifi• Exposure to Gen AI technology and tools About MetLife Recognized on Fortune magazine's list of the "World's Most Admired Companies" and Fortune World's 25 Best Workplaces™, MetLife, through its subsidiaries and affiliates, is one of the world's leading financial services companies; providing insurance, annuities, employee benefits and asset management to individual and institutional customers. With operations in more than 40 markets, we hold leading positions in the United States, Latin America, Asia, Europe, and the Middle East. Our purpose is simple - to help our colleagues, customers, communities, and the world at large create a more confident future. United by purpose and guided by our core values - Win Together, Do the Right Thing, Deliver Impact Over Activity, and Think Ahead - we're inspired to transform the next century in financial services. At MetLife, it's #AllTogetherPossible . Join us! #BI-Hybrid

Role Description - Analyse und Ausarbeitung konkreter Use Cases unserer Kunden zur Nutzung daten- und KI-basierter IT-Lösungen - Erstellung praktisch umsetzbarer Lösungskonzepte – technisch, fachlich und architektonisch - Entwicklung von PoC-, MVP- und produktreifen Anwendungen auf Cloud- und On-Premise-Stacks - Einsatz moderner LLM-Technologien: Embedding, Re-Ranking, Prompting, Fine-Tuning, Retrieval-Konzepte und weitere Methoden, sofern sie den Kundennutzen steigern - Enge Zusammenarbeit mit unseren Architekten, Beratern und Kunden zur Integration der Lösungen in bestehende Systemlandschaften - Mitarbeit bei der Weiterentwicklung unserer Produktlinien (QI-Box, QI-Flow) und unseres standardisierten Einführungsprozesses Qualifications - Mindestens 5 Jahre Berufserfahrung in AI/Data Science/Machine Learning/Data Engineering - Sehr gute Kenntnisse in Python sowie in gängigen ML-/DL-Frameworks (PyTorch, TensorFlow, Scikit-learn) - Fundierte Erfahrung mit LLMs, RAG-Systemen, Embeddings und Evaluationsverfahren - Sicherer Umgang mit relationalen Datenbanken, SQL sowie Vektor-Datenbanken - Erfahrung im Aufbau robuster Datenpipelines und grundlegende Kenntnisse in MLOps - Arbeit mit strukturierten Daten (z.B. Zeitreihen) und unstrukturierten Daten (Texte, PDFs, Dokumente) - Erfahrung mit Cloud- oder On-Premise-Umgebungen (AWS, Azure, GCP) - Verständnis für containerisierte Deployments, API-Design und Integrationen - Strukturierte und eigenständige Arbeitsweise - Präzise Kommunikation, Teamfähigkeit und Freude an interdisziplinärer Zusammenarbeit - Fähigkeit, komplexe technische Sachverhalte für Kunden verständlich aufzubereiten Benefits - Anspruchsvolle Projekte und viel eigene Verantwortung für Deine Arbeit - Offenheit für Veränderungen und die Bereitschaft, gemeinsam noch besser zu werden - Exzellentes technisches Equipment mit aktueller Hardware und freier Betriebssystemwahl - Flexibilität durch familienfreundliche Arbeitszeit im Rahmen der Vertrauensarbeitszeit - Mitarbeiter Benefits wie Jobrad, Fitness Abo, betriebliche Altersvorsorge, u.v.m.

Role Description Can you imagine a world where business and digital solutions will be truly seamless and where users will help companies to co-create them? Do you want to help us to shape this human-centred world? Welcome to UNGUESS. UNGUESS is the crowdsourcing platform for effective testing and real insights that enable tech, digital and business leaders to make smarter decisions, faster. How? Unleashing the power of the crowd, a community of highly engaged people all over the world that allows us to bring end-customer insights into the design, development, and testing phases of a product. This is not a traditional data engineering position. Around 60–70% of your work will focus on GenAI, RAG systems, vector search, and natural language understanding (NLU). The remaining part will cover classic data engineering responsibilities such as ETL pipelines and data modeling. You won’t just maintain existing systems, you’ll be the first building block of something new, laying the foundations for a knowledge base that transforms raw testing data into intelligent, queryable insights. As our first dedicated Data Engineer, you will be the architect of the infrastructure that makes this vision possible. You’ll own the design, implementation, and scalability of our data stack, working closely with the product and development teams. We are a rapidly growing tech company with the ambition of building an LLM-queryable Knowledge Base by leveraging existing but currently unstructured data sources. We do not yet have a dedicated data team: this role will be the first hire, with full ownership over architecture, implementation, and scalability. Responsibilities - Design and implement data ingestion and normalization pipelines from heterogeneous sources (APIs, files, databases, streams). - Build a data lake on AWS (S3, Glue, Athena) and orchestrate data flows using CDK. - Implement RAG (Retrieval-Augmented Generation) systems using vector databases and LLM models (Bedrock, OpenAI, LangChain). - Model metadata and define chunking strategies for NLU-queryable documents. - Ensure data security, governance, monitoring, and cost optimization. - Collaborate with the Product team to integrate the knowledge base into the existing platform. Requirements - GenAI & Vector Search: Hands-on experience with RAG systems in production, embedding models (OpenAI, Cohere, Amazon Titan), and vector databases (OpenSearch, Pinecone, pgvector). - Strong grasp of chunking strategies, retrieval optimization (precision/recall/reranking). - Proven expertise with AWS CDK, data services (S3, Glue, Athena, Lambda, Step Functions), and ML/AI workloads (Bedrock, SageMaker). Solid understanding of IAM, KMS, VPC for security/compliance. - Has a builder's mindset and enjoys designing robust, scalable solutions. Nice to have - Hands-on with serverless architectures and cost-optimized scaling strategies. - Experience in cloud-native environments and CI/CD (AWS). - Familiarity with monitoring and alerting (CloudWatch, X-Ray). Benefits - Compensation: €45,000 to €50,000/year gross salary and competitive MBO bonus - this range is a guideline; we’re first and foremost looking for the right person, the final offer will be shaped around you and reflect your skills and experience. - Remote work lovers. - Fast-track growth opportunities. - Access to group and personal training programs. Please note that this job advertisement is open to applicants of all genders, in accordance with Laws 903/77 and 125/91.

Hello and thank you for your interest! We're looking for folks nationwide who are great at data entry and typing. We offer a flexible work from home remote position that allows you to stay home with the family! The pay range is flexible from $16/ph to $30/ph DOE and level of experience. You'll meet these requirements to work from home remotely • Stable Internet connection • Work can be done using the following: Phone device, laptap or computer • Must be able to type accurately with a minimum speed of 30 words per minute • Able to focus on tasks without being distracted • Must be resident of the US • Not afraid of emailing clients as needed We're looking for folks who we can depend on who can work from home remotely without distraction and are go-getters. Pay range from 16 to 30 hourly depending on the role, level of experience and proven ability to work from home at the same level as from an office. Data entry clerks come from all different backgrounds including, data entry, telemarketing, customer service, sales, clerical, secretary, administrative assistant, warehouse, inventory, receptionist, call center, part-time, retail fields & more • Must be 16 year of age or older • Must be proficient with basic PC skills • Must have an internet connection • Basic english written language • Basic english spoken language Thank you for your interest!