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Five9

Data Engineer II

Five9

Senior Data Engineer focusing on designing and implementing data extraction solutions from enterprise systems at Five9. Collaborating with cross-functional teams to enhance productivity through AI-powered tools.

Posted 7/15/2026full-timeBengaluru • 🇮🇳 IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and maintaining scalable data pipelines using Google Cloud Platform services, with a strong focus on data extraction, transformation, and loading (ELT) processes. Proficient in managing infrastructure as code and optimizing data workflows for performance and reliability in finance-related environments.

Highest-signal resume keywords
Google Cloud Platform (GCP)Data Pipeline DevelopmentTerraform Infrastructure ManagementAdvanced SQL ProficiencyData Visualization with Looker

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Data EngineeringETL/ELT Job DesignApache AirflowPython ProgrammingREST/SOAP API IntegrationBigQueryDataformCloud Run FunctionsCI/CD MethodologiesAI Automation Tools
Soft Skills
Attention to DetailSelf-StarterTime ManagementProblem-SolvingCollaboration
Tools & Technologies
GitLabGoogle Data StudioCloud StorageWorkflowsPub/Sub
Certifications & Qualifications
Professional Cloud DeveloperProfessional Cloud Database Engineer
Industry Keywords
Finance Data ProcessingData WorkflowsCloud ArchitectureData IntegrityProduction Support

Tech Stack

Tools & technologies
AirflowApacheBigQueryCloudETLGoogle Cloud PlatformJavaJavaScriptPythonSOAPSQLTerraform

About the role

Key responsibilities & impact
  • Collaborate with stakeholders across the Finance team to understand business requirements and translate them into well-defined, actionable data sets for analysis and reporting.
  • Design, develop, and maintain scalable data extraction and ELT pipelines in Google Cloud Platform (GCP) to process structured and unstructured data from diverse sources including databases, REST/SOAP APIs, and cloud storage systems.
  • Leverage a suite of GCP services such as Big Query, Dataform, Cloud Run Functions, Workflows, Airflow, Pub/Sub, and Cloud Storage to build efficient, secure, and high-performing data workflows.
  • Manage infrastructure as code using Terraform and maintain code and CI/CD pipelines in GitLab following branching, review, and deployment best practices.
  • Build, test, and maintain AI agents and internal AI tooling to automate repetitive data engineering and finance workflows and improve productivity across the team.
  • Continuously monitor and optimize data pipelines for performance, scalability, reliability, and cost-efficiency.
  • Manage and monitor scheduled production jobs (Daily, Weekly, Bi-Weekly, and Monthly), ensuring timely and accurate data processing across all cycles during PST business hours.
  • Provide production support during critical month-end data load windows (Day 1 to Day 5), ensuring data availability and resolving issues swiftly to meet business reporting deadlines.
  • Maintain clear and thorough technical documentation and runbooks for data pipelines, workflows, integrations, and system architecture to support ongoing development and cross-functional collaboration.
  • Support Looker dashboards and ML models that serve finance and business stakeholders.
  • Identify opportunities for improvement in existing applications and workflows, recommending and implementing scalable solutions that enhance system functionality and user experience.
  • Provide insights by collecting, analyzing, and summarizing data-related development and operational issues to support troubleshooting and continuous improvement.
  • Manage multiple tasks and projects simultaneously, effectively prioritizing work across the full lifecycle of data engineering initiatives.
  • Respond to and fulfill ad-hoc data requests from business stakeholders, delivering timely and accurate datasets or insights to support decision-making and operational needs.

Requirements

What you’ll need
  • Bachelor's and/or master’s degree in computer science, Computer Engineering, or a related technical discipline.
  • 3–5 years of hands-on data engineering experience, with a strong understanding of the architectural differences between transactional systems and analytical data warehouses.
  • Hands-on experience with Google Cloud Platform (GCP) services, including BigQuery, Dataform, Cloud Run Functions, Workflows, and Pub/Sub.
  • Strong experience reading data from REST and SOAP APIs and building data applications using Python (JavaScript and Java a plus).
  • Proven expertise in building, deploying, and maintaining data pipelines using tools such as Apache Airflow / Cloud Composer and Dataform.
  • Experience managing infrastructure as code with Terraform.
  • Proficiency with GitLab, CI/CD tools and methodologies.
  • Experience designing and writing efficient ETL/ELT jobs to ingest and transform data into Google Cloud Storage and BigQuery, ensuring scalability, performance, and data integrity.
  • Advanced SQL proficiency, with the ability to write, optimize, and manage complex queries in high-volume data environments.
  • Strong skills in data visualization, with experience creating dashboards using Looker, Google Data Studio or similar BI tools; exposure to ML models is a plus.
  • Experience building or working with AI agents / AI-powered automation tools to improve productivity is highly desirable.
  • Experience supporting scheduled production jobs during critical finance month-end data load cycles, ensuring data accuracy, timeliness, and system reliability throughout the Day 1 to Day 5 close period.
  • Availability to work in the PST time zone to support production jobs and ad-hoc requirements.
  • Solid understanding of cloud architecture design principles, including performance and cost optimization.
  • Exceptional attention to detail, with a commitment to delivering high-quality, reliable work.
  • Self-starter with the ability to thrive in unstructured environments, manage ambiguity, and independently drive initiatives forward.
  • GCP certifications (e.g., Professional Cloud Developer, Professional Cloud Database Engineer) are a strong plus.

Benefits

Comp & perks
  • Health insurance
  • Flexible work arrangements
  • Professional development opportunities