Sql developer állások I. kerületben (adatbázisszakértő)

• Leading a data engineering team comprising 5-6 consultants
• Overseeing project delivery
• Managing and mentoring the team
• Ensuring successful execution of data engineering projects
• Ensuring successful execution of ML/MLOps projects
• Ensuring successful execution of cloud migration projects

• Establish data feeds with custodian banks, data vendors, and other service providers
• Support senior leadership, clients, and the broader Data Team in executing analyses and providing data-driven answers to questions
• Fully automate and centralize existing data integration processes

• Delivery of complex data engineering projects individually or by leading small delivery teams
• Management of customer relationships alone or in collaboration with a Project Manager
• Support of pre-sales process
• Mentoring of more junior engineers
• Contribution to hiring best-in-class data talent

Performing tasks related to the position....

• Delivery on complex data engineering projects across industries
• Leading small delivery teams
• Managing customer relationships alone or with a Project Manager
• Mentoring more junior engineers
• Evaluating the quality of junior engineers' work
• Contributing to hiring best-in-class data engineers

• Maintaining and evolving data structures
• Building new ETL flows and maintaining/improving existing ones
• Designing new data structures and data modelling concepts
• Ensuring data quality by verifying data consistency and accuracy
• Creating data validation methods

• Ownership of data engineering features, architecture, and code quality
• Design, implementation, and maintenance of Databricks-based data pipelines and workflows
• Building and optimization of ETL/ELT processes using Apache Spark on Databricks

• Implementation and support of VB.NET based software solution
• Participation in the run and maintain team

• Data gathering from various organizational sources
• Design and implementation of data integration processes
• Collaboration with business stakeholders for reporting requirements
• Extraction, transformation, and loading (ETL) of raw data

• Design and develop normalized and denormalized data models to support reporting and data integration needs
• Apply dimensional modelling techniques to create efficient, scalable, and business-oriented data models
• Develop and maintain data transformations and models using SQL and dbt

• Development, maintenance, and support of cloud-based data operation infrastructure and production data pipelines
• Design, implementation, operation, and optimization of Azure data services and Databricks workloads

• Technical leadership post-sales for strategic customers in big data project design and implementation
• Identification and driving of new initiatives to turn data into actionable business value aligned with business goals

• Technical leadership post-sales for strategic customers in big data projects
• Design and implementation of big data projects from architectural design to data engineering and model deployment

• Building and maintaining dataset ingestion, cleaning, and versioning pipelines
• Designing and operating labeling workflows including quality control and inter-annotator agreement tracking
• Owning dataset testing including coverage analysis, class balance, leakage detection, and dataset documentation

• Skálázható cloud-native adatarchitektúrák tervezése Databricks vagy MS Fabric platformokra
• Adatmodellek, sémák és tárolási minták kialakítása (lakehouse, Delta, Parquet)
• Batch és streaming adatok betöltési pipeline-jainak megtervezése
• ETL/ELT folyamatok és transzformációs stratégia meghatározása

• Microsoft SQL Server operation including maintenance, migrations, administration, configuration
• Support for developers, testers and DevOps engineers about best practices in database operation

• Managing and migrating ETL pipelines between various source systems
• Validating pipeline build success and output data quality
• Communicating with business stakeholders and SME's regarding their respective data domain

• Setup, operation, maintenance, and reliability of databases used for IT service operations and ITSM processes
• Operation-relevant databases supporting service management, monitoring, reporting, and operational tooling

• Technical leadership and mentoring of data engineers
• Technical oversight for Databricks solutions
• Design and implementation of scalable ETL/ELT pipelines using Databricks, Python/PySpark, SQL, and Delta Lake

• Adattárház fókuszú elemzői, tervezői feladatok ellátása
• Fejlesztési igények felmérése, elemzése és rendszerezése
• Rendszerszintű funkcionális-, integrációs-, adatmodellt érintő követelmények meghatározása
• Megoldási módok megtervezése, logikai architektúrába való illesztése