Data Cloud Engineer (DataOps)

About Trafilea

Trafilea is a dynamic and innovative Tech E-commerce Group that operates multiple direct-to-consumer brands in the intimate apparel and beauty sectors, with a focus on using data-driven strategies to scale their businesses. In addition to our products, we have our own online community dedicated to promoting body positivity. As a rapidly growing global player, Trafilea is committed to creating high-quality products and services that enhance the customer experience and drive long-term growth.

At Trafilea, we foster a culture of collaboration, innovation, and continuous learning. We believe in investing in our people and providing them with the support and development opportunities they need to grow both personally and professionally. With our remote-first approach, you'll have the freedom to work from anywhere in the world, surrounded by a diverse and talented team that spans the globe.

🌟 Role Mission

The Data Cloud Engineer is responsible for designing and maintaining scalable, secure, and efficient data platforms in the cloud. You will work closely with Data Engineers, DevOps, and Analytics teams to ensure high availability, performance, and reliability of our data infrastructure.

Your mission is to enable real-time and batch data processing, ensure data security and compliance, and optimize cloud resources to support large-scale analytics and machine learning workloads.

🛠️ Responsibilities

🔹 Cloud Data Infrastructure & Optimization

• Design and implement scalable data architectures in AWS (Redshift, Athena, Glue, S3, DynamoDB).

• Optimize data storage, processing, and retrieval strategies for performance and cost efficiency.

• Implement data lake and data warehouse solutions to support analytics and BI teams.

🔹 Security & Compliance

• Ensure data security, encryption, and access control policies are in place.

• Implement GDPR, SOC 2, and compliance best practices for data governance.

• Monitor and prevent data breaches, unauthorized access, and performance issues.

🔹 Observability & Performance Monitoring

• Implement monitoring and alerting solutions for data pipelines (Datadog, Prometheus).

• Troubleshoot performance bottlenecks and improve query execution times.

🔹 Collaboration & Knowledge Sharing

• Work closely with Data Scientists, BI Analysts, and DevOps teams to align data solutions with business needs.

• Document data workflows, best practices, and infrastructure standards.

• Provide guidance on data engineering best practices and mentor junior engineers.

What we offer

• Collaborate with world-class talents in a data-driven, dynamic, energetic work environment.

• Opportunity to grow and develop both professionally and personally.

• Safe space to be who you truly are, with a commitment to diversity, equity, and inclusion.

• Openness to new ideas and initiatives.

• Great benefits package including remote work, 15 working days of paid holidays, Learning subsidy, and more!

We've been recognized by Forbes and FlexJobs as one of the Top 25 Companies for Remote Workers. Apply now!

🎓 Qualifications

✅ Must-Have Skills

✔️ 3+ years of experience as a Data Cloud Engineer, Data Engineer, or Cloud Engineer.

✔️ Strong experience with AWS cloud services for data processing (Redshift, Athena, Glue, S3, DynamoDB, Kinesis).

✔️ Expertise in SQL and distributed databases (PostgreSQL, Snowflake, BigQuery, ClickHouse).

✔️ Hands-on experience with ETL/ELT pipelines, automation, and orchestration tools (Airflow, Step Functions, dbt).

✔️ Strong knowledge of Infrastructure as Code (Terraform, CloudFormation) for data infrastructure.

✔️ Experience working with large-scale data processing frameworks (Apache Spark, Flink, EMR).

✔️ Proficiency in Python, Bash, or similar scripting languages for automation.

✅ Nice-to-Have Skills

➕ Experience with streaming data architectures (Kafka, Kinesis, Apache Flink, RabbitMQ).

➕ Knowledge of machine learning pipelines and feature stores.

➕ Experience with Data Governance, Data Quality, and Security Best Practices.

➕ Understanding of FinOps principles for cost optimization in cloud data solutions.