• 8–10 years in Data Engineering and Data Analysis. • Strong hands-on experience in Informatica PowerCenter/IDQ for ETL design, development, and optimization. • Advanced skills in PySpark for large-scale data processing, transformation, and analytics. • Solid working knowledge of Hadoop technologies (HDFS, Hive, Sqoop, MapReduce). • Proficiency in Python and Kafka for streaming and batch data pipelines. • Strong understanding of database concepts, data design, data modeling, and ETL workflows. • Experience in analyzing, designing, and coding ETL programs including data extraction, ingestion, quality checks, normalization, and loading. • Hands-on experience with Agile methodology and Jira for project delivery. • Proven ability in client-facing roles with strong communication and leadership skills to coordinate across SDLC. • Exposure to AWS data components and analytics. • Familiarity with machine learning models and AI concepts. • Experience with data modeling tools such as Erwin.

• Responsible for acquiring, curating, and publishing data both on prem and in the cloud for analytical or operational uses. • Ensures the data is in a ready-to-use form. • Utilizes skills to translate business analytic requests/requirements. • Works with various technologies from big data, relational and non-relational databases. • Consults on data projects of intermediate complexity. • Practices code management and integration with current architectural and data governance guidelines. • Produces data building blocks and data flows for varying client requests. • Creates business user access methods to data. • Utilizes techniques such as mapping data and transforming data to satisfy business rules. • Translates business data stories into a technical story breakdown structure. • Develops and maintains moderately complex scalable data pipelines. • Executes on mid size projects and identifies opportunities to optimize data workflows.

• Design, develop, and maintain scalable data pipelines for data ingestion, processing, and transformation • Integrate data from multiple source systems (e.g., ERP, MES, engineering systems) • Ensure data quality, consistency, and reliability across the data platform • Implement and optimize data storage and processing solutions • Collaborate with Data Architects to align with target architecture and standards • Support Data Scientists and business teams by providing well-structured and accessible data • Monitor and troubleshoot data pipelines and workflows • Contribute to the development of a modern, cloud-based data platform • Apply software engineering best practices in data development

Role Description At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Data Annotators to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own - Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. - Labeling elements of a piece of content rather than the content as a whole. - Assigning predefined categories or labels to items. - Evaluating the perceived quality and/or appropriateness of content. - Generating labels to advance understanding of a concept, trend, etc. - Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. - Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. - Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. - Ordering or ranking items based on a set of preferences or criteria. - Creating prompts or questions that will be used to generate responses from a language model or other AI system. - Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). - Generating responses to prompts or questions using a language model or other AI system. - Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. - Producing concise summaries of longer pieces of text or data. - Converting spoken language or audio content into written text. - Converting text or spoken language from one language to another. - Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. Qualifications - A High School Diploma or higher is required. - Professional or Expert level proficiency (C1/C2) in English. Requirements - The expected hourly salary range for this position is $13 p/hour, based on experience, skills, and qualifications. Important Information Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at FTC Job Scams . If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov .