Onapsis
Cybersecurity
SeniorDataEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Data Engineer at Onapsis. Skills: Data Lakehouse, Data Pipelines, Cloud Technologies, AI/ML Integration. Architect and Design Scalable Data Solutions. Design/develop/maintain Data lakehouse solutions”
Industry & Context.
Problem-solving skills; Data integrity; Scalability; Performance optimization; Troubleshooting
What They're Looking For.
Must Have
5+ years experience as Data Engineer, Deep understanding of data architecture, Cloud-based ETL/ELT frameworks, AWS or Azure experience, Proficiency in Apache Spark, Proficiency in Kafka, Proficiency in Hadoop, Proficiency in Databricks, Proficiency with Python libraries, Python libraries for data processing, Python libraries for ML, Hands-on experience building real-time data processing, Hands-on experience building AI/ML-driven analytics, Ability to architect data lakehouse solutions, Ability to manage data lakehouse solutions, Ability to architect classic warehouse solutions, Ability to manage classic warehouse solutions, Familiarity with compliance requirements, Familiarity with audit requirements, Implementing data governance frameworks, Implementing data security frameworks, Problem-solving skills, Experience with CI/CD tools, Experience with data orchestration platforms
Nice to Have
Databricks experience is a bonus, Snowflake experience is a bonus, Synapse experience is a bonus, Experience with advanced data architecture principles, Experience using BI tools
What You'll Do.
Architect and Design Scalable Data Solutions
Design/develop/maintain Data lakehouse solutions
Implement ETL/ELT pipelines
Load data into a Lakehouse
Implement data models
Implement data processing frameworks
Ingest large datasets
Transform large datasets
Develop solutions integrating multiple data sources
Enable real-time analytics
Enable reporting across dashboards
Collaborate to co-develop AI-driven features
Identify patterns in client data
Identify anomalies in client data
Ensure compliance with industry standards
Ensure secure best practices
Implement data governance frameworks
Monitor data pipelines
Optimize cloud database architectures
Protect sensitive information
Work closely with stakeholders
Understand stakeholder data needs
Propose data solutions
Drive data-driven decision-making
Deliver actionable insights
Continuously monitor data pipelines
Continuously troubleshoot data pipelines
Continuously enhance data pipelines
Orchestrate workflows using Apache Airflow
Provide hands-on mentorship
Provide technical guidance to junior engineers
Conduct architecture discussions
Establish comprehensive documentation
Document data architecture
Document data governance
Document data processes
How You'll Work.
Team & Collaboration
Cross-functional teams; Engineering and DevOps; Security and IT professionals; Stakeholders including analysts; Engineers and product managers; Junior engineers
Communication Scope
Architecture discussions
Process & Methodology
Agile
Full Job Description
About the job The world’s most critical--and at risk--business applications have been neglected for far too long. Onapsis eliminates this blind spot by providing cybersecurity solutions dedicated to business-critical applications. Whether running on premises, in the cloud, or in a hybrid environment, Onapsis helps nearly 30% of the Forbes Global 100 understand the threats and risks across their SAP and Oracle landscapes. We are seeking a Senior Data Engineer to join our mission-driven team. This role is ideal for experienced data engineers with a proven track record in architecting scalable data pipelines, leveraging cloud technologies, and contributing to high-impact cybersecurity solutions. You will be responsible for building high-performance ETL frameworks, optimizing data platforms, and contributing directly to the enhancement of our customers' threat detection, response, and remediation capabilities. What you will be doing, your legacy: You will be working directly with company Principal Engineers evaluating, scoping, proposing, and building features to fulfill business solution requirements to protect our customers. You will play a direct role in laying the technical foundation for a new product offering. Additionally, you will be working with Engineering and DevOps to deliver high-quality products and services while also working closely with security and IT professionals to ensure safe and secure best practices are followed. Responsibilities: Architect and Design Scalable Data Solutions: Design/develop/maintain Data lakehouse solutions (Iceberg/Delta Lake /Hudi) applying industry best practices and structuring / optimizing the data according to data access patterns. Data Pipeline Development: Implement ETL/ELT pipelines using cloud technologies (Spark / pySpark / Glue, Kinesis Streams / Iceberg) to load the data into a Lakehouse for both efficient ML processing and UI reporting. Implement data models and data processing frameworks (Spark, Kafka, Snowflake) t
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