Spark Engineer

This position does not offer sponsorship. Candidates must be legally authorized to work in the United States without sponsorship now or in the future

Overall Purpose
This position plays a key role in the development, testing, and deployment of complex technical solutions, focusing on data strategy, architecture, and system health.

Key Responsibilities

• Develop data strategies to address complex and open-ended requirements.
• Lead technical and data architecture, design, and prototyping efforts to support product needs and broader data strategy.
• Build and manage technical plans, backlogs, and oversee execution through to production delivery.
• Lead and guide cross-functional teams, representing engineering in sessions and influencing others to drive decisions.
• Collaborate with product managers, designers, and engineering teams to conceptualize and build new features.
• Own features or systems, ensuring long-term health and addressing surrounding system health.
• Assist in identifying and resolving production issues in partnership with Support and Operations teams.
• Develop and implement tests to ensure application quality, performance, and scalability.
• Continuously seek to improve engineering and data standards, tooling, and processes.
• Support the company's commitment to risk management and protecting data integrity.

Minimum Qualifications

• Bachelor s degree in computer science or a related field.
• 10+ years of experience in data platforms, distributed systems, SaaS, cloud solutions, and microservices.
• 7+ years of experience in Data Warehouse, Big Data, and real-time & batch processing.
• 4+ years in developing Business Intelligence Solutions.
• 2+ years in Artificial Intelligence/Machine Learning development and model life cycle.
• Experience in delivering business-critical systems.
• Expertise in scalable system design and implementation.
• Hands-on experience with SQL Server, HDFS, Elastic Search, ETL processes, and data science solutions (Python, Spark, etc.).
• Experience with event-driven architectures and cloud platforms (AWS, Azure, Google Cloud).
• Familiarity with CI/CD, Agile, SDLC, and DevOps practices.
• Background and drug screen.

Preferred Qualifications

• Experience with Big Data platforms (Cloudera, Spark, Kafka).
• Familiarity with Aerospike, SOLR, AppDynamics, and real-time payment networks (RTP, FedNow).
• FinTech experience and Kubernetes expertise.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

This position does not offer sponsorship. Candidates must be legally authorized to work in the United States without sponsorship now or in the future

Overall Purpose
This position plays a key role in the development, testing, and deployment of complex technical solutions, focusing on data strategy, architecture, and system health.

Key Responsibilities

• Develop data strategies to address complex and open-ended requirements.
• Lead technical and data architecture, design, and prototyping efforts to support product needs and broader data strategy.
• Build and manage technical plans, backlogs, and oversee execution through to production delivery.
• Lead and guide cross-functional teams, representing engineering in sessions and influencing others to drive decisions.
• Collaborate with product managers, designers, and engineering teams to conceptualize and build new features.
• Own features or systems, ensuring long-term health and addressing surrounding system health.
• Assist in identifying and resolving production issues in partnership with Support and Operations teams.
• Develop and implement tests to ensure application quality, performance, and scalability.
• Continuously seek to improve engineering and data standards, tooling, and processes.
• Support the company's commitment to risk management and protecting data integrity.

Minimum Qualifications

• Bachelor s degree in computer science or a related field.
• 10+ years of experience in data platforms, distributed systems, SaaS, cloud solutions, and microservices.
• 7+ years of experience in Data Warehouse, Big Data, and real-time & batch processing.
• 4+ years in developing Business Intelligence Solutions.
• 2+ years in Artificial Intelligence/Machine Learning development and model life cycle.
• Experience in delivering business-critical systems.
• Expertise in scalable system design and implementation.
• Hands-on experience with SQL Server, HDFS, Elastic Search, ETL processes, and data science solutions (Python, Spark, etc.).
• Experience with event-driven architectures and cloud platforms (AWS, Azure, Google Cloud).
• Familiarity with CI/CD, Agile, SDLC, and DevOps practices.
• Background and drug screen.

Preferred Qualifications

• Experience with Big Data platforms (Cloudera, Spark, Kafka).
• Familiarity with Aerospike, SOLR, AppDynamics, and real-time payment networks (RTP, FedNow).
• FinTech experience and Kubernetes expertise.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.