We are seeking a skilled Mid-Level Data Developer to join our Data Developer team for a digital transformation project. You will play a crucial role in designing and implementing data pipelines, analytics infrastructure, and reporting solutions for a portal. As a Mid-Level Data Developer, you will be responsible for data migration from legacy systems, building ETL processes, and ensuring data quality and compliance.

- Design and implement ETL pipelines for migrating data from Microsoft Power Automate to modern data architecture

- Build and maintain data pipelines using AWS services (Glue, Lambda, Step Functions, Kinesis)

- Develop data models and schemas for PostgreSQL databases supporting multi-tenant architecture

- Create data integration processes for external systems (insurers, brokers, regulatory bodies)

- Implement data quality checks, validation rules, and monitoring for insurance data accuracy

- Build data transformation processes for multi-currency calculations and exchange rate management

- Develop analytics data marts for reporting dashboards, KPIs, and loss triangle calculations

- Create automated data export processes for Excel reports and regulatory submissions

- Implement data archiving and retention policies compliant with insurance regulations

- Design and maintain data cataloging and metadata management systems

- Build real-time data streaming solutions for notifications and SLA monitoring

- Develop data backup and disaster recovery processes ensuring RPO < 1 hour

- Create data lineage documentation and impact analysis for regulatory compliance

- Implement data masking and anonymization for PII and sensitive insurance information

- Monitor data pipeline performance and optimize for scalability across LATAM regions

- Collaborate with analysts and business stakeholders to understand data requirements

- Experience as a data developer with focus on ETL/ELT pipelines and data modeling

- Strong experience with AWS data services (S3, Glue, Lambda, RDS, Redshift, Kinesis)

- Proficiency in SQL and database design with PostgreSQL or similar relational databases

- Experience with Python for data processing and automation scripting

- Experience with SharePoint

- Knowledge of data pipeline orchestration tools (Apache Airflow, AWS Step Functions)

- Understanding of data warehousing concepts and dimensional modeling techniques

- Experience with data quality frameworks and validation processes

- Familiarity with streaming data processing (Apache Kafka, AWS Kinesis, Apache Spark)

- Knowledge of data formats (JSON, Parquet, Avro) and data serialization

- Experience with version control (Git) and CI/CD pipelines for data workflows

- Understanding of data security principles, encryption, and access controls

- Knowledge of data governance practices and metadata management

- Strong problem-solving skills and attention to data accuracy and consistency

- Experience working in Agile environments with cross-functional teams

- Excellent communication skills for collaborating with business stakeholders

- Experience with Apache Spark for large-scale data processing

- Familiarity with data visualization tools (Grafana, Tableau, Power BI)

- Knowledge of machine learning pipelines and MLOps practices

- Experience with Infrastructure as Code (Terraform, CloudFormation)

- Understanding of data lake architecture and modern data stack

- Experience with real-time analytics and event-driven architectures

- Knowledge of containerization (Docker, Kubernetes) for data workloads

- Familiarity with data catalog tools (AWS Glue Catalog, Apache Atlas)

- Experience with multi-region data replication and disaster recovery

- Understanding of cost optimization strategies for cloud data services

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