Software Developer – Analytics Data Platform, Data Reliability

This is a fully remote position, open to applicants in Canada.

📋 Description

• Design, construct, and manage scalable Spark batch pipelines, Airflow DAGs, services, and platform tools on AWS to ensure reliable analytics data for Genesys Cloud.

• Take ownership of the testing strategy and architecture for new platform capabilities.

• Establish unit, integration, API, data pipeline, and end-to-end validation processes for confident releases.

• Create automated testing frameworks and suites in Java and Python that integrate with Jenkins CI/CD and AWS Step Functions.

• Define and produce representative sampled, synthetic, and AI-generated test datasets.

• Implement data quality controls and release gates to ensure correctness, completeness, freshness, and reconciliation.

• Review designs and code for testability, risk, scalability, and performance, and establish evidence of production readiness.

• Develop MCP tools, agent skills, or agentic workflows using technologies such as Strands or LangGraph.

• Engage in on-call support and conduct root cause analysis.

• Create automated regression tests and data checks to minimize recurring incidents.

• Collaborate with developers, product teams, and platform consumers to establish acceptance criteria and data quality expectations.

• Share engineering expertise 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 paired with 2+ years of experience in software development, quality engineering, or test automation.

• Strong proficiency in Java with hands-on development experience in Python.

• Experience in developing automated tests utilizing frameworks such as JUnit, TestNG, pytest, or REST Assured, including integration or end-to-end testing for APIs, services, or data pipelines.

• Familiarity with CI/CD practices using Jenkins or a similar platform, along with Git-based development workflows.

• Working knowledge of AWS services like Amazon S3, Amazon EMR, Amazon EC2, AWS Lambda, AWS IAM, and Amazon CloudWatch.

• Practical experience with AI-assisted development tools such as Kiro, Claude, GitHub Copilot, or Cursor, demonstrating sound judgment in reviewing and validating AI-generated output.

• Proficient in SQL with the ability to investigate data, application behavior, and system signals to identify root causes.

• Willingness to participate in an on-call rotation and troubleshoot production incidents.

• Excellent written and verbal communication skills, capable of collaborating effectively and working independently within a distributed team.

• Hands-on experience with Apache Spark for large-scale batch processing, preferably using Amazon EMR.

• Experience in writing, testing, or operating Apache Airflow DAGs.

• Familiarity with AWS Glue, Amazon Athena, or Apache Iceberg.

• Background in data quality engineering, including pipeline output validation, reconciliation, data contracts, and schema-evolution testing.

• Experience in generating test data at scale using sampled, synthetic, or AI-generated datasets while adhering to 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 tools utilized across multiple engineering teams.

• Familiarity with multi-tenant SaaS platforms or privacy-related data lifecycle requirements, including GDPR data deletion.

• Experience building MCP tools, agent skills, or agentic workflows using frameworks like 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 working arrangements.

• 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.