We are looking for a highly responsible and proactive Data Service Engineer to ensure smooth operations across the company’s data ecosystem. This role plays a critical part in monitoring data workflows, resolving operational issues, supporting business users with data-related inquiries, and collaborating across multiple technical and business teams. The ideal candidate is detail-oriented, service-minded, and capable of working in a fast-paced, cross-functional environment.Key Responsibilities
Monitor and manage data ingestion and ETL processes from various sources.
Continuously improve data operational processes and suggest solutions to recurring issues.
Write SQL queries to extract, validate, and manipulate data from databases.
Handle incident tickets and coordinate resolution by escalating to relevant domain teams.
Support business users by assisting with data extraction, validation, and ad hoc requests.
Investigate and resolve data-related issues or anomalies in collaboration with relevant teams.
Proactively report daily incidents and operation summaries to the team.
Requirements
Bachelor’s degree in Computer Science, Information Systems, Statistics, or a related field.
Strong SQL skills and familiarity with relational databases.
Solid understanding of data lifecycle, data quality principles, and operational workflows.
Excellent attention to detail and analytical thinking.
Ability to communicate effectively with both technical and non-technical teams.
Self-motivated, with strong problem-solving and time-management skills.
Experience with ETL/ELT tools such as Azure Data Factory, Airflow, or Databricks.
Familiarity with cloud platforms (Azure, AWS) and data lakes/warehouses.
Experience with monitoring or visualization tools (Power BI).
Knowledge of scripting languages (e.g., Python) for automation or data manipulation.
