Data Engineering at Blackbaud is responsible for ingestion, transformation and processing of data that powers Blackbaud Data Intelligence and Advanced analytics products. The data managed by the team supports data science, data enrichment, research and data analysis as well as making data operationally able to be consumed ...
... Management Maintain and improve data interfaces for internal systems and external partners. Support interface file conversion and interface location management with Data Lake and/or CustomsAI. Drive process improvements through data enrichment (e.g., Coordinate technical requirements and provide resolutions through internal IT ...
... monitor performance, implement guardrails, and ensure AI systems remain accurate, compliant, and efficient in production.- AI Application Development : Analyze data and develop bespoke AI applications, including retrieval-augmented generation (RAG) pipelines and data enrichment services, that enhance decision-making and automate ...
... Uplift the metadata (semantic layer) of existing data ('Brownfield' enrichment) to support AI and Natural Language Query (NLQ) usage, accelerate adoption of Mesh data architecture, reduce consumer friction from poor catalog quality, and deliver data product prototypes that demonstrate the value of uplifted data assets Uses ...
... tuning, and testing ML algorithms (e.g., familiarity with modern ML/DL approaches. - Experience with prompt engineering and leveraging GenAI for classification, data enrichment, semantic embeddings, and innovative AI-driven solutions. - Experiment and rapidly prototype design frameworks, validate hypotheses efficiently, and ...
... tuning, and testing ML algorithms (e.g., familiarity with modern ML/DL approaches. - Experience with prompt engineering and leveraging GenAI for classification, data enrichment, semantic embeddings, and innovative AI-driven solutions. - Experiment and rapidly prototype design frameworks, validate hypotheses efficiently, and ...
... approaches based on the data and analytical objective. - Use visual analysis to support interpretation and data-driven decision-making. Dataset Annotation & Enrichment - Contribute statistical expertise to dataset annotation, labeling, and enrichment. - Support improvements to the quality and structure of datasets used for ...
... Syniti, SAP MDG, Informatica MDM, or any home grown Strong understanding of data governance operating models, data ownership, data stewardship, workflow approvals, data quality rules, metadata, and data lifecycle management. Experience in data profiling, cleansing, harmonization, enrichment, duplication management, migration ...
... Design and implement AI-assisted workflows such as document and data extraction, semantic classification, summarization, entity matching, anomaly triage, metadata enrichment, code assistance and natural-language interfaces to curated data. Build workflow components using large language model APIs, prompt templates, structured ...
... schema, and scalability for both human and crawler experience. Build AI-driven workflows Design and run AI-first processes using tools like ChatGPT, LLMOps, and data enrichment systems for smarter keyword discovery, clustering, and content mapping. Run content optimization pipelines Orchestrate content improvements with internal ...
... you an all-around data enthusiast with a knack for ETL We're hiring Data Engineers to help build and optimize the foundational architecture of our product's data. We've built a strong data engineering team to date, but have a lot of work ahead of us, Migrating from relational databases to a streaming and big data architecture, ...
... leader in data integrity, providing accuracy and consistency in data for 12,000 customers in more than 100 countries, including 90 percent of the Fortune 100. Our data integration, data quality, location intelligence, and data enrichment products power better business decisions to create better outcomes. We seek talented individuals ...
... AI-assisted tools to accelerate development — generating boilerplate code, drafting SQL/dbt models, writing documentation, debugging pipeline failures, and summarising data quality issues Partner with data quality, governance, and analytics teams to ensure data is well-modelled, well-documented, and trustworthy Optimise Snowflake ...
... leading the system design and implementation of technical solutions. Working with data excites you; You have created Big Data architecture, can build and operate data pipelines, and maintain data storage, all within distributed systems. You have a deep understanding of data modeling and experience with modern data engineering ...
Sigmoid Analytics is a leading Data solutions company backed by Sequoia Capital. We offer best in- end-to-end data value chain spanning across Data Science, Data Engineering and Data Ops. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. The below role is for our ...
... LLMs, AutoGen, OCR, Databricks, PySpark, Python, Azure DevOps, and enterprise AI platforms. The role requires strong hands-on experience across SQL Server, Azure Data Factory, Azure Data Lake, Microsoft Fabric, Logic Apps,Power BI, GitHub, and Data Modeling. Required Skills: - 10+ years of Software Engineering / Data Engineering ...
... business faces, which can be better understood with data Compile and analyze data related to business' issues Develop clear visualizations to convey complicated data in a straightforward fashion Qualifications - Bachelor's or Master's degree in Statistics or Applied Mathematics or equivalent experience - 1 - 2 years' Data ...
... performant Use AI tooling within DE workflows, including code generation, pipeline automation, and data quality checks Contribute to and help shape company-wide data governance standards Collaborate with analytics, BI, and business teams to deliver trusted, well-modeled data 5–7 years of hands-on data engineering experience ...
... security, and scalability while enabling faster and more reliable software delivery. Key Responsibilities: - Hands on experience working on Databricks, creating data pipelines, transformation rules using Unity Catalog, PySpark, SparkSQL - Hands on Databricks Devs – Deployments, CICD, Performance Management - Hands on Databricks ...
... data ecosystems. Lead the design, architecture, and delivery of large-scale data engineering solutions across cloud and hybrid environments. Drive end-to-end data platform implementations encompassing data ingestion, transformation, storage, processing, governance, and consumption. Architect batch and real-time data pipelines ...