Data Product Support Engineer

Acclime; Philippines; On-site; PHP 600,000 - 1,000,000; Full time

Job summary

Acclime in the Philippines seeks a data operations engineer to ensure smooth data processing and continuity of pipelines. You will monitor, triage, and recover from incidents while collaborating with data consumers to resolve issues promptly.

You will investigate errors, perform root-cause analysis, and communicate progress across global teams using Jira and Confluence. Strong English and analytical skills are essential for success in a fast-paced, client-facing environment.

Qualifications

• 2+ year experience in data engineer role
• 2+ year experience with customer support in data related projects
• Very good communication skills (verbal and written)
• Very good command of English (we work with global clients)
• Strong analytical thinking and problem-solving skills with proactive approach
• Familiarity with SQL databases, Snowflake, Git/Bitbucket
• Experience with Jira, Confluence, MS Excel
• Ability to work within a global support environment
• Handover to polish L2 support team at the end of local shift

Responsibilities

• Monitor daily data processing status through email alerts or internal ETL interfaces to detect anomalies
• Investigate processing errors by following SOPs, analyzing logs and reviewing history
• Troubleshoot and recover data pipeline incidents, coordinating with development and operations teams
• Communicate delays, root causes, and progress through Jira and internal channels
• Perform data quality checks and resolve detected anomalies or escalate to data owners
• Support end users with data-related questions, incidents, or change requests
• Maintain up-to-date knowledge base entries and contribute to process improvement

Skills

Communication

English fluency

Data engineer experience

Customer support experience

Analytical thinking

Root cause analysis

SQL databases

Snowflake

Git/Bitbucket

Jira

Confluence

MS Excel

Global support environment

Tools

Autosys

UC4

Job description

Ensure smooth data operations and continuity of data processing pipelines. The role combines technical monitoring, triage, incident recovery, and direct collaboration with data consumers. It requires both analytical and operational mindset owing the issue from detection to resolution.

Key responsibilities

• Monitor daily data processing status through email alerts, scheduling tools (Autosys, UC4), or internal ETL interfaces – t0 detect anomalies or signs of potential issues and taking a proper action for resolving the issues
• Investigate processing errors by following SOPs, analyzing Unix logs, and reviewing Snowflake query history.
• Troubleshoot and recover data pipeline incidents, coordinating with development and operations teams when needed.
• Communicate delays, root causes, and progress transparently through Jira and internal channels.
• Perform data quality checks and resolve detected anomalies or elevate to the correct data owners.
• Support end users with data-related questions, incidents, or change requests, ensuring clear documentation.
• Maintain up-to-date knowledge base entries and contribute to process improvement.

Required skills

Minimal

• Very good communication skills (verbal and written)
• Very good command of English (we work with global clients)
• 2+ year experience in data engineer role
• 2+ year experience with customer support in data related projects
• Strong analytical thinking and problem-solving skills with proactive approach
• Familiarity with below technologies to perform root cause analysis:
• Proven experience with SQL databases
• Proven experience with DWH, Snowflake
• Proven experience with core repository version control tools (Git, BitBucket)
• Jira, Confluence, MS Excel,
• Ability to work within a global support environment
• Handover to polish L2 support team at the end of local shift

Nice to have

• Proven experience supporting data products from both technical and data perspectives
• Experience with ETL monitoring tools (Autosys, UC4, or equivalent)
• Service-oriented attitude, patience, thoroughness and good attention to detail
• Familiarity with data quality tools or frameworks