Data Analytics Engineer

About the Role

We are seeking a talented and Data Analytics-oriented Software Engineer with expertise in Node.js, TypeScript. This role involves automating the creation of reports, analyzing data to identify issues and opportunities, and working closely with stakeholders to deliver insights that drive informed decision-making. Your work will play a critical role in streamlining data processes and ensuring that actionable insights are readily available across the organization.

Key Responsibilities

• Design and develop automated solutions to generate reports using Node.js and TypeScript.
• Build workflows and pipelines to aggregate, process, and visualize data efficiently.
• Ensure that reports are accurate, reliable, and delivered on schedule.
• Analyze large datasets to identify trends, anomalies, and opportunities for improvement.
• Work with stakeholders to define key performance indicators (KPIs) and ensure reports meet business requirements.
• Highlight issues in data quality, business processes, or system performance through clear, actionable insights.
• Create and maintain scalable data pipelines to gather and process data from multiple sources.
• Leverage APIs, databases, and external tools to integrate data into reporting workflows.
• Collaborate with cross-functional teams to understand reporting needs and data dependencies.
• Present insights and findings to technical and non-technical stakeholders in a clear and concise manner.
• Continuously improve data collection, transformation, and visualization processes to reduce latency and increase efficiency.
• Implement robust monitoring and error-handling mechanisms for reporting workflows.

Requirements

Key Qualifications

• Proficiency in Node.js and TypeScript with a strong understanding of backend development.
• Experience working with data processing libraries (e.g., CSV parsers, JSON transformers).
• Strong SQL skills for querying and analysing data from relational databases.
• Familiarity with data visualization tools or libraries such as Grafana.
• Experience working with APIs to pull and push data from/to external systems.
• Strong ability to analyse and interpret large datasets to extract meaningful insights.
• Experience with statistical analysis or machine learning concepts (preferred but not required).
• Familiarity with data formats like JSON, CSV, and XML.
• Excellent problem-solving skills and attention to detail.
• Strong written and verbal communication skills for presenting findings to stakeholders.
• A proactive mindset to identify and address potential issues or opportunities.
• Familiarity with data warehousing concepts (e.g., Redshift, Snowflake, BigQuery, Databricks).
• Knowledge of cloud platforms for data processing (e.g., AWS Lambda, Google Cloud Functions, or Azure).
• Experience automating reports with tools like PowerBI, Tableau, or similar.
• Understanding of event-driven architectures and message queues (e.g., Kafka, RabbitMQ).