
51 - 200 Mitarbeiter
🤝 B2B
🤖 Künstliche Intelligenz
🏢 Unternehmen
B2B • Artificial Intelligence • Enterprise
SunnyData ist ein auf Databricks spezialisiertes Unternehmen für Datenengineering und KI-Beratung, das Organisationen dabei unterstützt, ihre Datenplattformen zu modernisieren, bestehende EDWs und Data Lakes zu Databricks zu migrieren und KI/ML- sowie GenAI-Initiativen zu operationalisieren. Das Unternehmen bietet Databricks-zertifizierte Ingenieure, Migrationsbeschleuniger, Daten-Governance, MLOps und Branchenexpertise für Industriezweige wie Gesundheitswesen und Finanzdienstleistungen an.
🕒 vor 1 Monat
🗣️🇺🇸🇬🇧 Englisch erforderlich
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51 - 200 Mitarbeiter
🤝 B2B
🤖 Künstliche Intelligenz
🏢 Unternehmen
B2B • Artificial Intelligence • Enterprise
SunnyData ist ein auf Databricks spezialisiertes Unternehmen für Datenengineering und KI-Beratung, das Organisationen dabei unterstützt, ihre Datenplattformen zu modernisieren, bestehende EDWs und Data Lakes zu Databricks zu migrieren und KI/ML- sowie GenAI-Initiativen zu operationalisieren. Das Unternehmen bietet Databricks-zertifizierte Ingenieure, Migrationsbeschleuniger, Daten-Governance, MLOps und Branchenexpertise für Industriezweige wie Gesundheitswesen und Finanzdienstleistungen an.
• You will be part of a team responsible for supporting new and existing customers in their data engineering needs. • You will guide customers to make the best technical decisions to achieve their goals • You will actively work across multiple customer accounts which you would need to track and report on their progress. • You will design, build, and operationalize complex data solutions, correct problems, apply transformations, and recommend data cleansing /quality solutions. • You will analyze sources to determine value and recommend data to include in analytical processes. • You will incorporate core data management competencies including data governance, data security and data quality. • You will collaborate within and across teams to support delivery and educate end users on data products / analytic environments. • You will perform data and system analysis, assessment and resolution for defects and incidents of moderate complexity and correct as appropriate. • You will test data movement, transformation code, and data components.
• 5+ years of related experience in data engineering and data product development. • Experience in one or more of the following: • - Data Engineering technologies (e.g., Spark, Hadoop, Kafka) • - Databricks platform - data engineering and/or ML ops experience would be a huge bonus • - Data Science and Machine Learning technologies (e.g., pandas, scikit-learn, HPO) • - Data Warehousing (e.g., SQL, OLTP/OLAP/DSS) • Solid understanding of the end to end data analytics workflow • Proven problem solving skills including debugging skills • Strong verbal and written communication skills • Leadership - Intermediate leadership skills with a proven track record of self-motivation in identifying personal growth opportunities • Excellent time management and prioritization skills. Knowledge of public cloud platforms AWS, Azure, or GCP would be a plus • Domain Knowledge: Background working in the Financial Services industry, preferably in a banking environment. • Regulatory Compliance: Understand industry compliance requirements and standards, specifically in banking IT landscapes • Nice to have: Databricks Certification
• Innovative Environment: Work with cutting-edge technologies and industry leaders in data engineering and AI. • Customer Impact: Make a real difference in how businesses leverage data for strategic decision-making. • Career Growth: Opportunities for professional development and career advancement. • Collaborative Culture: Join a supportive team that values collaboration and knowledge sharing.
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