Senior Data Platform Engineer (Spark, AWS, Apache Iceberg, Production Systems)

Genesys empowers organizations of all sizes to improve loyalty and business outcomes by creating the best experiences for their customers and employees. Through Genesys Cloud, the AI-powered Experience Orchestration platform, organizations can accelerate growth by delivering empathetic, personalized experiences at scale to drive customer loyalty, workforce engagement, efficiency and operational improvements.

We employ more than 6,000 people across the globe who embrace empathy and cultivate collaboration to succeed. And, while we offer great benefits and perks like larger tech companies, our employees have the independence to make a larger impact on the company and take ownership of their work. Join the team and create the future of customer experience together.

Join the Analytics Lakehouse team to design and operate mission-critical, highly scalable data services in a fast-moving, experiment-driven environment.

You’ll work at the intersection of data engineering and quality, building robust pipelines, scalable architectures, and secure, testable systems.

What you’ll do

• Design, build, and maintain high-scale data ingestion and hydration pipelines
• Develop reliable, scalable backend services supporting a distributed, multi-tenant platform
• Diagnose and resolve complex system and test failures end-to-end
• Lead and contribute to system design, architecture discussions, and code reviews with a strong quality focus
• Ensure systems meet non-functional requirements: scalability, availability, latency, memory efficiency, security, and compliance (including HIPAA)
• Implement and maintain unit, integration, and end-to-end tests integrated into CI/CD pipelines
• Mentor and support teammates; contribute to engineering and testing best practices across global teams
• Evaluate and adopt new technologies; take ownership of features and operational excellence

Minimum requirements

• 5+ years of relevant experience; BS in Computer Science or equivalent practical experience
• Proven Big Data experience, including hands-on work with large-scale data processing systems
• Strong experience with Apache Spark (PySpark or Scala Spark)
• Solid data platform experience (data lakes, ETL pipelines, data modeling, governance)
• Experience building and operating REST APIs and multi-service (microservices/serverless) architectures
• Proficiency in at least one of Java, Scala, or Python
• Strong understanding of distributed systems (scalability, synchronization, fault tolerance)
• Experience with messaging systems and integration patterns
• Strong written and verbal communication skills

Core technical skills

• PySpark / Apache Spark (DataFrame API, SQL, partitioning, performance tuning)
• At least one JVM language (Java or Kotlin) for services or serverless workloads
• Build and test tooling: Gradle or Maven, pytest, tox
• Git workflows, code reviews, CI/CD pipelines
• Observability: logging, monitoring, and alerting

AWS & Data Platform Experience

• AWS Glue (ETL jobs, Data Catalog, performance tuning, auto-scaling)
• AWS Lambda (Python or Java), S3 (lifecycle policies, KMS, event-driven patterns)
• SQS/SNS, IAM (roles, policies, cross-account access), CloudFormation
• Columnar data formats and partitioning strategies
• ETL design patterns (batch processing, idempotency, partition overwrite)
• Workflow orchestration (DAGs)
• Testing/QA tooling (e.g., moto for AWS mocking, CI integration)
• Experience with microservices or serverless architectures

Nice to have

• Apache Iceberg, AWS Lake Formation (fine-grained access control)
• Apache Airflow; query engines such as Athena, Trino, Redshift Spectrum
• Serverless Framework
• Cost optimization (e.g., Glue/EMR tuning)
• Jenkins pipelines (Groovy)

Culture & expectations

We’re looking for engineers who raise the bar for those around them. You’ll be expected to:

• Act as a talent multiplier through mentoring and knowledge sharing
• Challenge assumptions and drive continuous improvement
• Take ownership and pride in delivering high-quality solutions
• Stay curious and continuously learn

Our benefits

At Genesys, we support your well-being, growth, and work–life balance:

• Flexible work options – Hybrid setup with remote flexibility and access to our Galway office
• Career development – Continuous learning, mentorship, and growth opportunities
• Pension scheme – Competitive employer-supported plan
• Annual bonus – Rewarding your impact and contributions
• Health coverage – Private health insurance, dental plan, and wellness support
• Financial protection – Income protection, life assurance, and financial planning resources
• Family-friendly policies – Generous maternity and paternity leave

#LI-MC1

If a Genesys employee referred you, please use the link they sent you to apply.

About Genesys:

Genesys® empowers more than 8,000 organizations worldwide to create the best customer and employee experiences. With agentic AI at its core, Genesys Cloud™ is the AI-Powered Experience Orchestration platform that connects people, systems, data and AI across the enterprise. As a result, organizations can drive customer loyalty, growth and retention while increasing operational efficiency and teamwork across human and AI workforces. To learn more, visit www.genesys.com.

Reasonable Accommodations:

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Genesys is an equal opportunity employer committed to fairness in the workplace. We evaluate qualified applicants without regard to race, color, age, religion, sex, sexual orientation, gender identity or expression, marital status, domestic partner status, national origin, genetics, disability, military and veteran status, and other protected characteristics.

Please note that recruiters will never ask for sensitive personal or financial information during the application phase.