Sr. Manager - Data Engineering
Manila, Philippines
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingLead, mentor, and grow a team of data engineers spanning junior to senior levels, including hiring and performance management.
Own the technical strategy and roadmap for the revenue data mart, supporting revenue recognition, billing, forecasting, and executive reporting.
Ensure reliable data integration with business systems such as Marketo, Salesforce, Anaplan, and NetSuite, maintaining consistency across the revenue lifecycle.
From the employer’s posting
Responsibilities: Lead, mentor, and grow a team of data engineers spanning junior to senior levels, including hiring and performance management. Own the technical strategy and roadmap for the revenue data mart, supporting revenue recognition, billing, forecasting, and executive reporting.
Lead, mentor, and grow a team of data engineers spanning junior to senior levels, including hiring and performance management. Own the technical strategy and roadmap for the revenue data mart, supporting revenue recognition, billing, forecasting, and executive reporting. Architect and oversee data pipelines integrating and transforming data across Hadoop, Oracle, Snowflake, AWS S3, and PostgreSQL.
Architect and oversee data pipelines integrating and transforming data across Hadoop, Oracle, Snowflake, AWS S3, and PostgreSQL. Ensure reliable data integration with business systems such as Marketo, Salesforce, Anaplan, and NetSuite, maintaining consistency across the revenue lifecycle. Partner with BI teams to structure the data mart for reporting and dashboarding in tools such as Tableau and Sigma.
What you’ll bring
All qualificationsCore experience
- 10+ years of experience in data engineering, with 3+ years in a management or technical leadership role.
- Experience with revenue recognition, billing systems, or subscription/SaaS revenue data.
- Proven experience managing a team of data engineers across varying experience levels.
- Familiarity with data governance, lineage, and cataloging tools.
- Hands-on expertise with Hadoop ecosystem tools (Hive, Spark, HDFS), Oracle, Snowflake, AWS S3, and PostgreSQL.
- Experience with CI/CD for data pipelines (e.g., dbt, Jenkins, GitHub Actions).
Qualification wording
10+ years of experience in data engineering, with 3+ years in a management or technical leadership role.
Experience with revenue recognition, billing systems, or subscription/SaaS revenue data.
Proven experience managing a team of data engineers across varying experience levels.
Familiarity with data governance, lineage, and cataloging tools.
Hands-on expertise with Hadoop ecosystem tools (Hive, Spark, HDFS), Oracle, Snowflake, AWS S3, and PostgreSQL.
Experience with CI/CD for data pipelines (e.g., dbt, Jenkins, GitHub Actions).
Tools in this posting
- Python
- SQL
- AWS
- dbt
- Hadoop
- Hive
- Oracle
- S3
- Sigma
- Snowflake
- Spark
- Tableau
- Airflow
- PostgreSQL
Source — Tool mentions in context
- Solid grasp of SQL performance tuning and large-scale data processing. - Strong experience in Python for data pipeline development, automation, and data processing. - Experience with cloud data architecture and cost/performance optimization on AWS.
- Deep understanding of ETL/ELT design, dimensional data modeling, and orchestration tools (e.g., Airflow, Control-M). - Solid grasp of SQL performance tuning and large-scale data processing. - Strong experience in Python for data pipeline development, automation, and data processing.
- Own the technical strategy and roadmap for the revenue data mart, supporting revenue recognition, billing, forecasting, and executive reporting. - Architect and oversee data pipelines integrating and transforming data across Hadoop, Oracle, Snowflake, AWS S3, and PostgreSQL. - Ensure reliable data integration with business systems such as Marketo, Salesforce, Anaplan, and NetSuite, maintaining consistency across the revenue lifecycle.
- Establish and enforce data governance, security, and compliance standards (e.g., SOX considerations). - Optimize pipeline performance and cost across on-prem (Hadoop, Oracle) and cloud (Snowflake, AWS) environments. - Own incident management and root-cause resolution for pipeline issues impacting revenue reporting.
- Proven experience managing a team of data engineers across varying experience levels. - Hands-on expertise with Hadoop ecosystem tools (Hive, Spark, HDFS), Oracle, Snowflake, AWS S3, and PostgreSQL. - Strong background building data marts or warehouses, ideally supporting finance or revenue use cases.
- Strong experience in Python for data pipeline development, automation, and data processing. - Experience with cloud data architecture and cost/performance optimization on AWS. - Excellent stakeholder management skills across Finance, Analytics, and Engineering.
- Background in a high-growth SaaS or telecom environment. - Experience migrating on-prem systems (Hadoop/Oracle) to cloud-native platforms (Snowflake/AWS). - Direct experience building integrations from Marketo, Salesforce, Anaplan, or NetSuite into a data warehouse.
- Primary mandate: build and maintain the data mart supporting RingCentral's revenue platform. - Core technology stack: Hadoop, Oracle, Snowflake, AWS S3, PostgreSQL. - Key connected business systems: Marketo, Salesforce, Anaplan, NetSuite, and other revenue-adjacent platforms.
- Familiarity with data governance, lineage, and cataloging tools. - Experience with CI/CD for data pipelines (e.g., dbt, Jenkins, GitHub Actions). - Background in a high-growth SaaS or telecom environment.
- Ensure reliable data integration with business systems such as Marketo, Salesforce, Anaplan, and NetSuite, maintaining consistency across the revenue lifecycle. - Partner with BI teams to structure the data mart for reporting and dashboarding in tools such as Tableau and Sigma. - Identify opportunities to apply ML/AI techniques (e.g., anomaly detection, forecasting) to improve pipeline reliability and revenue insights.
- Working knowledge of business systems that feed or consume revenue data, such as Marketo, Salesforce, Anaplan, and NetSuite. - Familiarity with BI tools such as Tableau and Sigma, and how data mart design impacts downstream reporting. - General knowledge of ML/AI concepts (e.g., predictive models, anomaly detection) and how they apply to data pipelines and analytics; hands-on ML development is not required.
- Key connected business systems: Marketo, Salesforce, Anaplan, NetSuite, and other revenue-adjacent platforms. - Downstream BI/reporting tools: Tableau, Sigma. What we offer:
- Strong background building data marts or warehouses, ideally supporting finance or revenue use cases. - Deep understanding of ETL/ELT design, dimensional data modeling, and orchestration tools (e.g., Airflow, Control-M). - Solid grasp of SQL performance tuning and large-scale data processing.
Benefits in the posting
Full benefits wording- Comprehensive HMO package (medical and dental)
- Paid time off and paid sick leave
- Quarterly Performance Bonus
- Employee Assistance and Wellness Programs
From the employer’s posting.
Job description
Senior Manager - Data Engineering
Say hello to opportunities.
If you’re looking to be part of what’s next in communication, you’re in the right place.
At RingCentral, we believe the best customer experiences happen when humans and AI work together. Our agentic voice AI portfolio—AIR, AVA, and ACE—brings together automation, assistance, and insights across the entire conversation lifecycle. The result? More seamless, intelligent experiences for businesses everywhere.
With $2.5B+ in ARR and $250M invested in R&D annually, we’re building the future of AI-powered business communications.
This is where you and your skills come in. We’re currently looking for:
We are looking for a Senior Manager of Data Engineering to lead a team of data engineers, from junior to senior level, responsible for building and scaling the data infrastructure that powers RingCentral's revenue platform. This role owns the design, development, and delivery of a revenue data mart into a reliable, well-governed source of truth for finance, sales, and executive reporting.
This is a hands-on leadership role: you'll set technical direction, mentor and grow engineers at all levels, and partner closely with Finance, Revenue Operations, Analytics, and Product stakeholders to ensure the data mart meets business needs for accuracy, timeliness, and scalability.
Responsibilities:
- Lead, mentor, and grow a team of data engineers spanning junior to senior levels, including hiring and performance management.
- Own the technical strategy and roadmap for the revenue data mart, supporting revenue recognition, billing, forecasting, and executive reporting.
- Architect and oversee data pipelines integrating and transforming data across Hadoop, Oracle, Snowflake, AWS S3, and PostgreSQL.
- Ensure reliable data integration with business systems such as Marketo, Salesforce, Anaplan, and NetSuite, maintaining consistency across the revenue lifecycle.
- Partner with BI teams to structure the data mart for reporting and dashboarding in tools such as Tableau and Sigma.
- Identify opportunities to apply ML/AI techniques (e.g., anomaly detection, forecasting) to improve pipeline reliability and revenue insights.
- Drive engineering best practices: data modeling, ETL/ELT design, orchestration, testing, CI/CD, and data quality/observability.
- Partner with Finance, Revenue Operations, and Analytics to translate business requirements into scalable data solutions.
- Manage sprint planning, prioritization, and delivery using Agile/Scrum practices.
- Establish and enforce data governance, security, and compliance standards (e.g., SOX considerations).
- Optimize pipeline performance and cost across on-prem (Hadoop, Oracle) and cloud (Snowflake, AWS) environments.
- Own incident management and root-cause resolution for pipeline issues impacting revenue reporting.
- Evaluate and introduce new tools and architectural patterns to modernize the data platform.
- Communicate progress, risks, and technical tradeoffs to senior leadership and non-technical stakeholders.
Qualifications:
- 10+ years of experience in data engineering, with 3+ years in a management or technical leadership role.
- Proven experience managing a team of data engineers across varying experience levels.
- Hands-on expertise with Hadoop ecosystem tools (Hive, Spark, HDFS), Oracle, Snowflake, AWS S3, and PostgreSQL.
- Strong background building data marts or warehouses, ideally supporting finance or revenue use cases.
- Deep understanding of ETL/ELT design, dimensional data modeling, and orchestration tools (e.g., Airflow, Control-M).
- Solid grasp of SQL performance tuning and large-scale data processing.
- Strong experience in Python for data pipeline development, automation, and data processing.
- Experience with cloud data architecture and cost/performance optimization on AWS.
- Excellent stakeholder management skills across Finance, Analytics, and Engineering.
- Experience with Agile/Scrum delivery.
- Working knowledge of business systems that feed or consume revenue data, such as Marketo, Salesforce, Anaplan, and NetSuite.
- Familiarity with BI tools such as Tableau and Sigma, and how data mart design impacts downstream reporting.
- General knowledge of ML/AI concepts (e.g., predictive models, anomaly detection) and how they apply to data pipelines and analytics; hands-on ML development is not required.
- Some experience with agentic AI (e.g., LLM-based agents, tool-calling workflows, or agent frameworks) and how it can be applied to data engineering and analytics workflows.
Preferred:
- Experience with revenue recognition, billing systems, or subscription/SaaS revenue data.
- Familiarity with data governance, lineage, and cataloging tools.
- Experience with CI/CD for data pipelines (e.g., dbt, Jenkins, GitHub Actions).
- Background in a high-growth SaaS or telecom environment.
- Experience migrating on-prem systems (Hadoop/Oracle) to cloud-native platforms (Snowflake/AWS).
- Direct experience building integrations from Marketo, Salesforce, Anaplan, or NetSuite into a data warehouse.
- Experience incorporating ML/AI capabilities into data platforms, such as automated data quality checks or forecasting models.
Team & Scope
- Direct management of a team of data engineers (Junior to Senior level).
- Primary mandate: build and maintain the data mart supporting RingCentral's revenue platform.
- Core technology stack: Hadoop, Oracle, Snowflake, AWS S3, PostgreSQL.
- Key connected business systems: Marketo, Salesforce, Anaplan, NetSuite, and other revenue-adjacent platforms.
- Downstream BI/reporting tools: Tableau, Sigma.
What we offer:
- Comprehensive HMO package (medical and dental)
- Paid time off and paid sick leave
- Quarterly Performance Bonus
- Employee Assistance and Wellness Programs
RingCentral’s work culture is the backbone of our success. And don’t just take our word for it: we are recognized as a Best Place to Work by BuiltIn, the Top Work Culture by Comparably and hold local BPTW awards in every major location. Bottom line: We are committed to hiring and retaining great people because we know you power our success.
About RingCentral/Acquire Intelligence
RingCentral is a global leader in agentic voice AI–powered business communications, delivering an integrated platform for business phone, SMS, contact center, workforce engagement management, video collaboration, and messaging. As the communications layer connecting businesses and customers, RingCentral is the front door of business communication and is in the advantageous position to apply AI at every phase of the conversation journey — before, during, and after each interaction. Our agentic AI portfolio includes autonomous voice-first AI agents that automate calls, assist in the moment, and analyze every interaction – enabling businesses to work smarter, respond faster, and connect more meaningfully with their customers. Visit ringcentral.com to learn more.
RingCentral is an equal opportunity employer that truly values diversity. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We are committed to providing reasonable accommodations for individuals with disabilities during our application and interview process. If you require such accommodations, please click on the following link to learn more about how we can assist you.
Acquire Intelligence transforms the way companies grow and operate by combining intelligent global outsourcing with AI consulting and implementation to accelerate growth and transform business at scale.
We eliminate inefficiencies, automate with intent, and reallocate work to where it performs best. With 9,000 employees across Australia, the Philippines, the Dominican Republic, and the United States, we provide secure and scalable solutions in customer experience, back office, and digital operations.
Founded in 2006, Acquire offers flexible delivery models ranging from building Remote Teams to comprehensive outsourcing in both onshore and offshore locations. Our AI division accelerates
transformation with automation strategies that deliver guaranteed ROI. All solutions are backed by deep expertise and enterprise grade compliance.
At Acquire Intelligence, we are Safe, Flexible, and Innovative. We deliver transformation with intent, impact, and entrepreneurial energy.
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Manila, Philippines
We eliminate inefficiencies, automate with intent, and reallocate work to where it performs best. With 9,000 employees across Australia, the Philippines, the Dominican Republic, and the United States, we provide secure and scalable solutions in customer experience, back office, and digital operations. Founded in 2006, Acquire offers flexible delivery models ranging from building Remote Teams to comprehensive outsourcing in both onshore and offshore locations. Our AI division accelerates transformation with automation strategies that deliver guaranteed ROI. All solutions are backed by deep expertise and enterprise grade compliance.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Oct 6, 2026
- Recorded sightings
- 6
- Last seen by us
- Oct 9, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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