At a glance
- Location
- Malta
About the role
- This role is dedicated to the operational maintenance, governance, and delivery lifecycle of data assets.
- The DataOps Engineer is responsible for user access provisioning, data platform permission management, deployment releases of analytical pipelines, and service observability.
- The position ensures optimal data quality through active monitoring, incident resolution, design incident prevention plans, and engagement with data requests.
Responsibilities
- Manage and audit Service Accounts, AWS IAM policies for data pipelines, and Role-Based Access Control (RBAC) schemas and Role & Permission management on Snowflake.
- Execute and automate deployment releases for data pipeline codebases, orchestration logic and database schemas.
- Configure, monitor, and optimize pipeline alerting thresholds in Amazon CloudWatch and Coralogix to log task execution failures and data delivery delays.
- Manage workflows, task schedules, and environment permissions using Apache Airflow.
- Actively design and implement preventive operations strategies, analysing system trends, pipeline bottlenecks, and job failures to eliminate systemic risks before SLA breaches occur.
- Formulate and maintain sophisticated observability patterns, building real-time dashboards and threshold-based notification alerts inside Coralogix to flag delays, capacity exhaustion, or anomalies.
- Perform root-cause analysis on runtime pipeline anomalies and complex data flow errors, collaborating across analytics engineering teams to design permanent, scalable operational remediation.
- Perform rigorous investigations into data quality, identifying discrepancies and implementing corrective actions in collaboration with other teams.
- Monitor query runtimes and compute consumption metrics to identify underutilized resources, proposing optimizations to maintain technical excellence and cost-efficiency.
- Drive AI-powered innovation in Data Operations by identifying opportunities to leverage AI, intelligent agents and automation.
Requirements
- Good experience configuring security structures, service integration privileges, and RBAC governance within enterprise data layers (e.g., Snowflake and AWS IAM).
- Proven expertise managing, deploying workflows, and debugging task execution failures in Apache Airflow.
- Advanced skill in engineering cloud monitoring rules, logging metrics, and automated alert structures using Amazon CloudWatch and Coralogix.
- High proficiency in writing complex SQL queries for dataset analysis and metadata tracking.
- Strong scripting capability in Python or shell environments to automate operational checklists, administrative tasks, and compliance auditing.
Preferred qualifications
- Familiarity with broader modern data environments (AWS Glue, S3, Athena and Redshift).
- Exposure to data observability concepts and data contract mechanisms.
- Good Data Analysis experience to identify trends and track Data Quality issues.
- Excellent verbal and written English Communication skills.
- Strong interpersonal and communication skills with a customer-centric mindset.
- Strong self-learning mindset to explore new technologies, documentation, and industry best practices independently.
- Must hold a valid AWS Certification focused on Operations/Support (such as AWS Certified SysOps Administrator).
- A valid Snowflake Certification (such as Snowflake SnowPro Core Certification).
Skills
- Snowflake
- AWS IAM
- Apache Airflow
- Amazon CloudWatch
- Coralogix
- SQL
- Python
- AWS Glue
- S3
- Athena
- Redshift
