Data Analyst

About the Role

The Data Analytics Engineer is responsible for designing, developing, and maintaining scalable data pipelines, curated datasets, and cloud-based analytics solutions that support audit analytics and data-driven decision-making. Working closely with audit teams and data analysts, this role ensures the availability, quality, security, and governance of enterprise data while enabling efficient reporting, automation, and advanced analytics.

Key Responsibilities

• Data Engineering & Integration
• Design, develop, and maintain scalable data pipelines for multiple data sources.
• Integrate data from APIs, SQL databases, and enterprise systems.
• Build and maintain curated datasets to support business and audit analytics.
• Automate data ingestion, transformation, and validation processes.
• Ensure historical accuracy through effective data versioning and time-stamping.
• Optimize data workflows for reliability and performance.
• Data Quality & Governance
• Perform data quality validation and integrity checks.
• Monitor data completeness, consistency, and accuracy across systems.
• Maintain data lineage, field definitions, and metadata documentation.
• Ensure compliance with data governance and audit requirements.
• Develop documentation for data integration processes and standards.
• Support continuous improvements in enterprise data management practices.
• Cloud Platform Administration
• Maintain and support cloud-based analytics infrastructure.
• Manage platform security, vulnerability remediation, and system patching.
• Oversee data backups, disaster recovery, and code repository management.
• Monitor cloud resources to ensure system availability and performance.
• Support infrastructure optimization and cloud automation initiatives.
• Implement best practices for secure cloud operations.
• Analytics & Automation
• Develop automated ETL workflows using Python and SQL.
• Build reusable datasets and analytical solutions for audit teams.
• Improve reporting efficiency through automation and process optimization.
• Support advanced analytics initiatives using modern data engineering practices.
• Assist in developing self-service analytical applications.
• Evaluate emerging technologies to enhance analytics capabilities.
• Collaboration & Technical Support
• Partner with audit teams and data analysts to understand business requirements.
• Provide technical guidance on available datasets and analytical tools.
• Mentor team members on data engineering best practices.
• Support knowledge sharing through documentation and training.
• Collaborate with cross-functional stakeholders to deliver data-driven solutions.
• Contribute to continuous improvement initiatives across analytics functions.

Qualifications

• Required:
• Bachelor's degree in Computer Science, Data Science, Information Technology, Engineering, or a related technical field.
• Minimum of five years of experience in data engineering, data analytics, or a similar role.
• Strong experience integrating data from APIs, SQL databases, and enterprise systems.
• Advanced proficiency in Python, including Pandas, NumPy, SQLAlchemy, and ETL development.
• Strong SQL programming and database management skills.
• Experience with cloud platforms such as AWS or Azure.
• Knowledge of cloud services including object storage, virtual machines, serverless computing, data integration, query services, and identity management.
• Strong analytical, troubleshooting, and problem-solving skills.
• Excellent communication and documentation abilities.
• Fluent English language skills.
• PREFERRED:
• Experience supporting internal audit, risk management, or compliance functions.
• Knowledge of audit evidence management and data lineage.
• Experience with artificial intelligence or machine learning technologies.
• Familiarity with Infrastructure as Code tools such as Terraform.
• Experience mentoring technical teams and supporting enterprise analytics initiatives.

Benefits

• Professional learning and career development opportunities.
• Unlimited access to online learning resources and educational materials.
• Collaborative and supportive work environment.
• Flexible working hours.
• Home office opportunities.
• Comprehensive health and wellness benefits.
• Life insurance.
• Employee assistance program.
• Internet allowance.
• Corporate discounts.
• Sports and wellness program.
• Paid annual leave.
• Birthday leave.
• Paid volunteer days for social responsibility initiatives.
• Employee recognition and additional workplace benefits.

Ideal Candidate

This opportunity is ideal for professionals who:

• Enjoy building scalable data engineering solutions.
• Have a passion for automation, cloud technologies, and analytics.
• Thrive in collaborative and cross-functional environments.
• Take ownership of data quality, governance, and system reliability.
• Communicate technical concepts effectively to both technical and non-technical audiences.
• Continuously seek opportunities to improve data infrastructure and business processes.

Equal Opportunity Employer

Netcombase is committed to fostering an inclusive workplace where diversity, collaboration, innovation, and equal opportunity are valued. All qualified applicants are encouraged to apply regardless of background or protected characteristics.