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Key skills for this role
Design and deploy a cloud-native analytics platform optimized for performance and scalability.
Develop and manage an API-driven data infrastructure ensuring secure and efficient data access.
Construct end-to-end data ingestion pipelines to integrate diverse data sources.
Apply AI techniques for data classification and harmonization to enhance data integrity.
Oversee data modeling, microservice orchestration, and platform monitoring and alerting.
Optimize Spark clusters and identify performance bottlenecks.
Assemble and deliver large, complex datasets that align with business requirements, automating data processes.
Architect ETL infrastructure using SQL and AWS big data technologies.
Collaborate with cross-functional teams to resolve data-related issues.
5-8 years of software engineering experience within a B2B SaaS environment.
Proven ability to manage substantial data volumes and intricate code structures.
Expertise in creating scalable Data Warehouse solutions for analytical reporting.
Strong analytical skills for handling unstructured datasets.
Experience in designing data transformation, metadata management, and workload management processes.
Working knowledge of message queuing, stream processing, and big data storage systems.
Experience with implementing data governance and quality control measures.
Proficiency in Python and Jupyter Notebooks.
Familiarity with SQL and NoSQL databases like MySQL, PostgreSQL, and Cassandra.
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Experience with big data technologies such as Spark and Kafka.
Experience with cloud platforms (AWS).
Experience with data pipeline management tools (Airflow, Luigi)
Verified company details for this employer are not available yet.
Full-time
Senior · 5+ years experience
Hybrid
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