Requirements

Expected technologies

SQL

PySpark

ETL

REST API

Azure DevOps

Cloud

Jira

AWS

Microsoft Azure

Google Cloud Platform

Prometheus

Grafana

Datadog

Python

Bash

Our requirements

• At least 5 years of experience in IT system maintenance, operation, and administration, with a focus on monitoring and troubleshooting
• Proficiency in SQL
• Familiarity with PySpark/Apache Spark for troubleshooting data processing tasks
• Expertise in data integration and ETL processes, ensuring smooth system operations and data flows
• Minimum 5 years of experience with APIs and system integrations, especially in the context of different data sources and systems
• Over 5 years of experience with Jira, Azure DevOps, and the ability to create change requests and report bugs
• Solid understanding of cloud computing platforms (AWS, Azure, Google Cloud) and cloud-based data storage solutions
• Experience with monitoring and alerting tools (e.g., Prometheus, Grafana, Datadog)
• Strong understanding of data security best practices, particularly concerning data integrity and confidentiality
• Scripting knowledge (e.g., Python, Bash) for task automation, such as data validation or system checks
• Knowledge of logs, ability to read and analyse them, and set up alerts based on log data to monitor system health
• Very good English skills
• Residing in Poland required

Optional

• Experience with financial crime compliance tools (analytic tools or case management tools from providers like LexisNexis or Oracle) is highly beneficial
• Previous work in the anti-financial crime domain is advantageous
• Strong problem-solving skills and the ability to propose system improvements

Your responsibilities

• Monitor, ensure, and improve the health and performance of the application and system
• Collaborate with reporting and data-providing teams to ensure system integration, data accuracy, and smooth operations
• Work with external vendors to report issues, request changes, and track bug resolutions
• Analyse system data to identify and resolve issues, using available tools and data integration processes
• Oversee data transformation using PySpark in Apache Spark, ensuring smooth and efficient data flows through the system
• Troubleshoot system and data pipeline issues as they arise
• Read and analyse system logs to diagnose issues, optimize performance, and set up alerts based on log data to monitor system health