Data Service Engineer

The Data Service Engineer supports the day-to-day reliability of enterprise data services. The role monitors data pipelines, investigates production failures, resolves data-quality and integration issues, coordinates incident follow-up, and helps ensure that trusted data is available to reporting, analytics, and downstream business processes.

Key Responsibilities

1. Data Pipeline Operations

·    Monitor scheduled and event-driven ETL/ELT pipelines across Azure Data Factory, Databricks, Airflow, and related platforms.

·    Investigate failed jobs, delayed data, missing records, schema changes, and dependency issues.

·    Rerun or recover pipelines using approved operational procedures and confirm successful completion.

·    Support production releases, cutovers, and post-deployment monitoring.

2. Incident and Problem Management

·    Respond to data-service incidents and operational requests within agreed service levels.

·    Perform root-cause analysis and document the issue, impact, resolution, and preventive action.

·    Create, update, and follow operational tickets through closure.

·    Coordinate with source-system owners, data engineers, infrastructure teams, and report owners when cross-team support is required.

3. Data Quality and Reliability

·    Validate data completeness, accuracy, freshness, and reconciliation results.

·    Maintain monitoring, alerting, and operational checks for critical pipelines and datasets.

·    Identify recurring failure patterns and recommend permanent fixes or automation.

·    Escalate material data risks with clear impact and status communication.

4. Stakeholder and Service Support

·    Support users of reports, dashboards, and downstream data products.

·    Provide concise updates on incidents, blockers, ownership, and expected next actions.

·    Participate in daily operational reviews and handovers.

·    Maintain runbooks, troubleshooting guides, support knowledge, and service documentation.

5. Continuous Improvement

·    Automate repetitive operational tasks and recovery steps where appropriate.

·    Contribute to observability, cost, performance, and reliability improvements.

·    Support standardization of deployment, support, and data-quality practices.

·    Share lessons learned and help improve team operational readiness.

Required Qualifications

·    Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related discipline, or equivalent practical experience.