Software Developer – Analytics Data Platform, Data Reliability

🔥 3 minutes ago

🇨🇦 Canada – Remote

💵 $102.9k - $135k / year

⏰ Full Time

🟢 Junior

🟡 Mid-level

📊 Analytics Engineer

👻 Ghost score 0%

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Genesys

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 1990

💼 Consulting

🏥 Healthcare

🛡️ Insurance

Consulting • Healthcare • Insurance

Genesys is a leading provider of AI-powered experience orchestration solutions designed to deliver personalized experiences at scale. Their offerings include comprehensive contact center software, workforce engagement management solutions, and an open platform with cloud architecture. Genesys Cloud CX and EX platforms optimize both customer and employee experiences using intelligent automation and embedded AI, allowing seamless engagement across any channel. With a focus on various industries including banking, healthcare, retail, insurance, and government, Genesys assists organizations in transforming customer and employee interaction landscapes. Additionally, their AppFoundry Marketplace offers pre-integrated applications to extend platform functionalities.

📋 Description

• Design, build, and operate scalable Spark batch pipelines, Airflow DAGs, services, and platform tooling on AWS for reliable Genesys Cloud analytics data • Own test strategy and test architecture for new platform capabilities • Define unit, integration, API, data pipeline, and end-to-end validation for confident releases • Develop automated Java and Python test frameworks and suites integrated into Jenkins CI/CD and AWS Step Functions • Define and generate representative sampled, synthetic, and AI-generated test datasets • Implement data quality controls and release gates for correctness, completeness, freshness, and reconciliation • Review designs and code for testability, risk, scalability, and performance and establish production-readiness evidence • Build MCP tools, agent skills, or agentic workflows using technologies such as Strands or LangGraph • Participate in on-call support and root cause analysis • Create automated regression tests and data checks to reduce recurring incidents • Partner with developers, product teams, and platform consumers to define acceptance criteria and data quality expectations • Share engineering knowledge across a distributed team

🎯 Requirements

• Master's degree in Computer Science or a related field, or a bachelor's degree in Computer Science or a related field plus 2+ years of experience in software development, quality engineering, or test automation • Strong proficiency in Java and hands-on development experience with Python • Experience developing automated tests using frameworks such as JUnit, TestNG, pytest, or REST Assured, including integration or end-to-end testing for APIs, services, or data pipelines • Experience with CI/CD practices using Jenkins or an equivalent platform, along with Git-based development workflows • Working knowledge of AWS services such as Amazon S3, Amazon EMR, Amazon EC2, AWS Lambda, AWS IAM, and Amazon CloudWatch • Practical experience using AI-assisted development tools such as Kiro, Claude, GitHub Copilot, or Cursor, with sound judgment in reviewing and validating AI-generated output • Experience with SQL and ability to investigate data, application behaviour, and system signals to identify root causes • Ability and willingness to participate in an on-call rotation and troubleshoot production incidents • Clear written and verbal communication skills, with ability to collaborate effectively and work independently within a distributed team • Hands-on experience with Apache Spark for large-scale batch processing, preferably using Amazon EMR • Experience writing, testing, or operating Apache Airflow DAGs • Familiarity with AWS Glue, Amazon Athena, or Apache Iceberg • Experience with data quality engineering, including pipeline output validation, reconciliation, data contracts, and schema-evolution testing • Experience generating test data at scale using sampled, synthetic, or AI-generated datasets while respecting applicable privacy requirements • Experience with performance or scalability testing for batch processing or distributed systems • Knowledge of pipeline observability practices, including metrics, logs, tracing with OpenTelemetry, and alerting • Experience contributing to shared test frameworks or platform tooling used across multiple engineering teams • Experience with multi-tenant SaaS platforms or privacy-related data lifecycle requirements, including GDPR data deletion • Familiarity with building MCP tools, agent skills, or agentic workflows using frameworks such as Strands or LangGraph

🏖️ Benefits

• Comprehensive extended group health coverage • Generous paid time off, including vacation and personal leave • Retirement savings program with employer RRSP matching up to a prescribed maximum amount • Family-friendly benefits, including parental leave top-up and adoption assistance • Growth and development opportunities through access to learning resources and internal mobility programs • Flexible ways of working • Mentorship, learning programs, leadership development and education support • Paid volunteer time • August Free Fridays • Well-being resources • Regionally tailored programs for employees and their families

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