... direction you want. Responsibilities Implement data ingestion from diverse sources utilizing technologies including RDBMS, REST API, flat files, Streams, Time series data, SAP Research and utilize Big Data technologies for effective data ingestion Process and transform data using tools such as Spark and various Cloud Services Understand ...
... evolve ML systems deployed across multiple countries and markets, accounting for differences in data distributions, regulations, and constraints. Mentor other data scientists through hands-on technical guidance, design reviews, and shared ownership of systems. Raise the bar for engineering practices across the Data Science ...
... Branża: bankowość Szukamy Data Engineera do rozwoju i migracji warstwy danych w obszarze AML. Kluczowym elementem roli jest budowa i rozwój rozwiązań opartych o Databricks i PySpark, integrujących dane z wielu źródeł oraz rozwój procesów ETL. Zakres obowiązków Rozwój i utrzymanie rozwiązań w Databricks z wykorzystaniem PySpark. ...
... Tasks Migrate Airflow DAGs and data workflows to ADF Build and maintain data pipelines, transformations, and data models Support and troubleshoot end to end data flows, from source systems to reports Collaborate with Power BI developers and business stakeholders Expectations Strong data engineering experience, including ...
Hitachi Energy seeks an experienced Project Manager to lead initiatives focused on data management and analytics. You will drive delivery, coordinate stakeholders across IT, procurement, engineering, and production, and implement best practices for data maintenance and quality. You will oversee schedules, milestones, and ...
... governance workflows and accelerate delivery Requirements 2+ years of experience in data governance or data consulting roles Strong proficiency in Informatica Cloud Data Governance and Catalog implementation Knowledge of metadata management and data quality practices in enterprise environments Understanding of Databricks and AWS ...
... systems, defining APIs and integration contracts, and producing architecture artifacts (e.g., HLD/LLD, sequence and deployment diagrams)Familiarity with modern data and processing technologies such as data streaming, real-time and batch processing, with exposure to Databricks; Kubernetes is a plusSignificant experience with ...
... professional experience in data architecture or platform engineering, with a proven track record of migrating legacy SAP systems to cloud-native platforms like SAP Datasphere. Deep technical understanding of SAP BDC Datasphere architecture, administration, and hands-on data modeling, paired with strong proficiency in SQL for ...
We are looking for a Senior Data Engineer to support the design, development, and enhancement of our client’s enterprise data platform. The ideal candidate is a hands-on data engineer with strong experience building data pipelines, integrating data from operational databases, and working with modern cloud data warehouses. ...
... enhancement process of master data objects with additional fields in standard and custom tables, screens, and tabs, including building custom validations for data governanceHands-on experience with SAP configuration (IMG) and creating custom Fiori apps for master data maintenance (article, vendor, customer, site, assortments)Familiarity ...
... kilkunastoletnie doświadczenie we współpracy partnerskiej z dużymi klientami. Wierzymy także, że praca powinna dawać ludziom satysfakcje, a nie być tylko obowiązkiem. Choć czasami znalezienie odpowiedniego dla siebie miejsca wymaga czasu i dobrego ukierunkowania przez bardziej doświadczonych kolegów. Każdy pracownik przychodzi do nas ...
... enhancement process of master data objects with additional fields in standard and custom tables, screens, and tabs, including building custom validations for data governanceHands-on experience with SAP configuration (IMG) and creating custom Fiori apps for master data maintenance (article, vendor, customer, site, assortments)Familiarity ...
... direction you want. Responsibilities Implement data ingestion from diverse sources utilizing technologies including RDBMS, REST API, flat files, Streams, Time series data, SAP Research and utilize Data Software Engineering technologies for effective data ingestion Process and transform data using tools such as Spark, Databricks ...
... governance workflows and accelerate delivery Requirements 2+ years of experience in data governance or data consulting roles Strong proficiency in Informatica Cloud Data Governance and Catalog implementation Knowledge of metadata management and data quality practices in enterprise environments Understanding of Databricks and AWS ...
... governance workflows and accelerate delivery Requirements 2+ years of experience in data governance or data consulting roles Strong proficiency in Informatica Cloud Data Governance and Catalog implementation Knowledge of metadata management and data quality practices in enterprise environments Understanding of Databricks and AWS ...
... accuracy, consistency, and quality of our material master data across systems. You will be part of material team responsible for maintaining high standards for data quality and contributing to the ongoing development of harmonized, efficient data management practices. - Master Data Management: Create, maintain, and update ...
... ground up, this hands-on program will equip you with the knowledge and practical experience to build intelligent data solutions. You’ll explore key areas such as: Data Integration, Data Visualization and Data Quality. By the end of the program, you’ll not only understand the full lifecycle of data products – you’ll be ready ...
... as data platform and Lakehouse buildouts, enterprise data warehouse modernization, cross-platform data migrations, advanced analytics, ML/AI activation, and data governance transformationsFrame target-state data visions with clients—connecting business priorities to data strategy, operating models, KPIs, and transformation ...
... as data platform and Lakehouse buildouts, enterprise data warehouse modernization, cross-platform data migrations, advanced analytics, ML/AI activation, and data governance transformationsFrame target-state data visions with clients—connecting business priorities to data strategy, operating models, KPIs, and transformation ...
... efficient data models integrating multiple sources in the form of Data Hub defining patterns, templates, and best practices for data engineering establishing data governance, access policies, and security frameworks for data layer / Data Hubs ensuring efficient storage, retrieval, and processing of large-scale datasets ...