ETL Data Engineer, Python, Snowflake

🕒 il y a 1 mois

🔔 Pennsylvania – Distant

🔔 Pennsylvania – Remote

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

🔙 Ingénieur Back-end

👻 Score fantôme 12%

Ce que ça veut dire : la probabilité que personne ne recrute vraiment pour cette offre.Comment le lire : 60 % ou plus, on pense que c'est une offre fantôme. Un score plus bas est moins inquiétant.Comment on la calcule : ancienneté, republications, postes ouverts vs taille de l'équipe, rapidité de clôture, et si le salaire est indiqué.À noter : une estimation à partir de données publiques, pas un jugement sur l'entreprise. De vraies offres peuvent avoir un score élevé, alors prenez-le comme un indice, pas comme un fait.

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Hamilton Lane

Site WebLinkedInTous les Emplois

501 - 1000 employés

Fondée en 1991

💼 Conseil

🛡️ Assurance

💸 Finance

💰 €77 500 000 Post-IPO Equity - Hamilton Lane en 2025-09

Consulting • Insurance • Finance

Hamilton Lane est une société de gestion d'actifs mondiaux des marchés privés qui propose des stratégies d'investissement et des solutions dans les secteurs des capitaux primaires, des dettes secondaires, du crédit direct, des actions directes, des infrastructures et des actifs réels, de l'immobilier, du capital-risque et de la croissance, ainsi que de la gestion de patrimoine privé. L'entreprise offre des services personnalisés et institutionnels, des plateformes de données propriétaires et technologiques pour informer les investissements et les rapports, ainsi qu'une éducation et des solutions gérées pour une large base de clients comprenant des investisseurs institutionnels, des investisseurs en gestion de patrimoine et d'assurance. Avec des actifs significatifs sous gestion et un accent mis sur les marchés privés, Hamilton Lane combine la gestion d'investissements, des solutions axées sur le client et une technologie basée sur les données.

Description

• Design, develop, and maintain scalable ETL/ELT data pipelines using Python (PySpark), Snowflake, and cloud-native integration technologies • Build reliable, efficient, and reusable data ingestion, transformation, and loading processes for enterprise analytics and reporting • Design, build, and optimize modern Snowflake cloud data solutions • Implement and manage Snowflake databases, schemas, tables, views, streams, tasks, stages, and stored procedures • Leverage Snowflake virtual warehouses, data sharing, time travel, and automated scaling for performance and cost efficiency • Design and implement scalable enterprise data warehouse solutions using dimensional modeling, star schemas, facts, and dimensions • Extract and ingest data from REST APIs, relational databases, SaaS applications, flat files, and cloud storage platforms • Develop and maintain ingestion frameworks for structured and semi-structured data • Contribute to data lakes, lakehouses, data mesh architectures, enterprise data catalogs, and integrations between Snowflake and Azure/cloud-native services • Collaborate with data architects and business stakeholders on logical and physical data models • Establish and enforce data engineering standards and best practices • Implement automated data quality controls, validation frameworks, and monitoring processes • Support data governance initiatives and organizational standards • Monitor and optimize Snowflake workloads, ETL/ELT processes, and SQL queries • Analyze warehouse utilization and recommend performance and cost-efficiency improvements • Monitor pipelines and platform operations, diagnose issues, and implement long-term reliability solutions • Support production environments and participate in incident resolution • Maintain documentation for pipelines, data flows, transformations, data models, and operational processes • Partner with cross-functional teams to understand requirements and provide technical data expertise • Implement access controls, masking policies, governance frameworks, and other security, privacy, and compliance measures

🎯 Exigences

• Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related field; or equivalent professional experience • Relevant certifications such as SnowPro, Azure Data Engineer Associate, or other cloud data platform certifications are a plus • Proven experience developing data pipelines extracting, transforming, and loading data from REST APIs, relational databases, cloud storage, and flat-file sources • Experience with Snowflake features including virtual warehouses, streams, tasks, stages, Snowpipe, secure data sharing, and performance optimization • Advanced SQL development skills, including complex queries, performance tuning, and optimization of large-scale data workloads • Experience with dimensional modeling, star schemas, fact tables, and dimension tables • Familiarity with cloud-based data ecosystems and integration services, particularly Microsoft Azure • Experience with Git and Azure DevOps or similar platforms for source code and CI/CD pipelines • Knowledge of data integration best practices, data governance frameworks, and enterprise data management principles • Strong analytical and problem-solving skills with exceptional attention to detail • Excellent verbal and written communication skills and ability to work collaboratively in a fast-paced environment with evolving priorities • Experience with big data technologies, machine learning, data science platforms, or advanced analytics is preferred • Experience with Power BI, Tableau, or similar data visualization tools is a plus • Familiarity with Agile delivery methodologies and DevOps practices is desirable • Preferred technologies include Snowflake, Python/PySpark, SQL, Azure Data Lake Storage, Azure Data Factory or equivalent orchestration tools, Azure Key Vault, Git/Azure DevOps, Power BI, REST APIs, CI/CD, and Terraform preferred

🏖️ Avantages

• Healthcare coverage • Mental health resources • Health & fitness reimbursement program • Wellness Rewards Program • Tuition and certification reimbursement programs • Continual education and development trainings • Paid time off to volunteer • Compensation for referring qualified candidates who join the team • Adoption reimbursement program • Paid time off for new parents and newlyweds • Travel support for nursing parents • Employer contributions to retirement programs • Employee stock purchasing plan

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