Data & Analytics Opportunities

As a freelance Data Specialist, you will contribute to advanced data pipelines, analytics platforms, and machine-learning initiatives with international teams on business-critical solutions.

Key Responsibilities

Data Engineers

• Design, build, and maintain robust data pipelines, ETL/ELT processes, and lakehouse architectures, including BigQuery, Redshift, and Databricks.
• Develop and optimize scalable data infrastructure using Python, Spark/Scala, Airflow, and DataProc.
• Deploy and maintain data platforms on GCP and/or AWS using services such as BigQuery, Cloud Storage, Glue, S3, and Redshift.
• Implement infrastructure as code using Terraform and CloudFormation to ensure consistency, traceability, and compliance.
• Contribute to secure, governed data environments by embedding auditability, data-quality controls, and access policies.

Data Scientists

• Build, validate, and deploy predictive and machine-learning models in production environments.
• Extract insights from structured and unstructured data using Python-based ML frameworks.
• Collaborate with analysts and engineers to operationalize AI/ML pipelines in governed, cloud-native ecosystems.
• Support model monitoring, versioning, and explainability in line with enterprise data standards.

Data Analysts

• Translate business questions into actionable insights through data storytelling and visual analytics.
• Build and maintain dashboards and analytical models using SQL, Python, and visualization tools including Looker, Tableau, and Power BI.
• Work with stakeholders to define KPIs and align data outputs with strategic goals.
• Ensure data integrity and quality within reporting environments.

Key Requirements

• Minimum 3 years of experience in Data Engineering, Data Science, or Data Analytics roles.
• Proven proficiency in Python and strong experience with modern cloud data platforms, especially GCP or AWS.
• Hands-on experience with ETL orchestration tools such as Airflow and Glue, version control with GitLab, and data-processing frameworks including Spark and DataProc.
• Familiarity with Infrastructure-as-Code tools such as Terraform and CloudFormation, plus CI/CD integrations for data pipelines.
• Experience working with data lakes, warehouses, or lakehouse architectures.
• Strong understanding of data governance, compliance frameworks, and secure data design.
• Excellent communication and collaboration skills in cross-functional teams.
• Fluent spoken and written English.

Nice to Have

• Experience with SOC 1, SOC 2, or ISO 27001-compliant data environments.
• Knowledge of real-time data streaming, metadata management, or lineage tracking.
• AWS or GCP certification in Data Analytics or Solutions Architecture.
• Sector experience in banking, telecom, AdTech, or retail analytics.