Data Engineer (ETL & Cloud Data Pipelines)

About the Role:

We are a fast-growing technology company building scalable, data-driven solutions across multiple domains. Our teams leverage modern pipelines, cloud-native infrastructure, and advanced analytics to deliver reliable, high-quality data at scale.

We’re seeking a Data Engineer to design, build, and operate end-to-end data pipelines and platforms. You will collaborate with analytics, ML, and product teams to ingest, transform, and serve data that powers dashboards, reporting, and AI/ML workflows.

What You'll Do At CYBLE:

Pipeline Development:

• Architect and implement ETL/ELT workflows using tools like Apache Airflow, dbt, or equivalent
• Build batch and streaming pipelines with Kafka, Spark, Beam, or similar frameworks
• Ensure reliable ingestion from diverse sources (APIs, databases, logs, message queues)

Data Modeling & Warehousing:

• Design, optimize, and maintain star schemas, data vaults, and dimensional models
• Work with cloud warehouses (Snowflake, BigQuery, Redshift) or on-premise systems

Data Quality & Governance:

• Implement validation, profiling, and monitoring to ensure data accuracy and completeness
• Enforce data lineage, schema evolution, and versioning best practices

Platform Operations:

• Containerize and deploy pipelines via Docker/Kubernetes or managed services
• Build CI/CD for data workflows and maintain observability (Prometheus, Grafana, ELK, DataDog)
• Optimize performance and cost of storage, compute, and network resources

Collaboration & Documentation:

• Partner with analytics, ML, and product teams to translate requirements into data solutions
• Document data designs, pipeline configurations, and operational runbooks
• Participate in code reviews, capacity planning, and incident response

What You’ll Need:

• 3+ years of professional data engineering experience
• Proficiency in one or more languages: Python, Java, or Scala
• Strong SQL skills and experience with relational databases (PostgreSQL, MySQL)
• Hands-on experience with at least one orchestration framework (Airflow, Prefect, Dagster)
• Familiarity with cloud platforms (AWS, GCP, or Azure) and their data services
• Experience with data warehousing solutions (Snowflake, BigQuery, Redshift)
• Solid understanding of streaming technologies (Apache Kafka, Pub/Sub)
• Ability to write clean, well-tested code and ETL configurations
• Comfortable working in Agile/Scrum teams and collaborating cross-functionally

Preferred (Nice-to-Have)

• Experience with data transformation tools (dbt, Matillion, Fivetran)
• Knowledge of workflow engines or orchestration beyond ETL (Temporal, Airflow XComs)
• Exposure to vector databases or embeddings pipelines for AI/ML use cases
• Familiarity with LLM integration concepts—prompting, RAG, feature store design
• Contributions to open-source data tools or active participation in data engineering communities

What We Offer

• Impactful Projects: Build the data foundation for high-growth analytics and AI initiatives
• Cutting-Edge Tech: Work with modern pipelines, cloud services, and real-time streaming
• Professional Growth: Access mentorship, training budgets, and conference stipends

Apply now to join our Data Engineering team and shape the data backbone that powers our next-generation solutions!

If you like working in an inclusive environment, you want to advance your career quickly, and your opinion is valued, look no further than Cyble, Inc. We are young, hungry, and ready to impact the cybersecurity landscape!

Cyble, Inc. takes into consideration an individual’s skillset, experience and location in making final salary determination.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected Veteran status age, or genetics, or any other characteristic protected by law.

A minimum of three rounds of interviews, plus an online assessment