• As a Senior Data Engineer, you will be the ideal person to support the Engineering area; your primary responsibility will be the scalable maintenance and creation of solutions for the data infrastructure. • Inspect, clean, transform, and model information, which is fundamental for decision-making. • Support the design of data processing components on Layer7 infrastructure that meet the specific needs of the company and its clients and suppliers. • Design, implement, and maintain data pipelines to integrate different sources. • Actively collaborate with data analysts, engineers, and cross-functional teams to understand and translate data requirements and propose tailored solutions. • Build metrics and implement observability tools to track and measure data pipeline performance for early incident detection. • Support the data governance process, maintaining data privacy criteria and the security regulations established by Layer7. • Document architectures, data flows, and process automation.

• You'll work across the full lifecycle of data engineering - from designing elegant solutions to deploying them in production • Building and maintaining data pipelines of varying complexity - from straightforward transformations to advanced probabilistic algorithms that drive our data science capabilities • Designing thoughtful solutions for new challenges, with emphasis on clean architecture and maintainability • Writing automated tests because we believe quality is built in, not bolted on • Fixing bugs and improving existing systems - our codebase evolves constantly • Exploring data when problems require investigation and analysis • Contributing to backend services and internal tools that support our data infrastructure • Deploying your work - you own it from concept to production

• Architect, scale, and maintain the backbone of our data ecosystem. • Transform massive volumes of raw signals into actionable intelligence. • Bridge the gap between high-level data strategy and hands-on technical excellence. • Lead the design, implementation, and optimization of distributed data architectures to support massive Batch & Streaming pipelines. • Ensure scalability, security, and performance of the infrastructure, maintaining high system availability (99.9%+) for analytics platforms. • Optimize storage solutions to balance high-speed processing with cost-efficiency. • Collaborate with software engineers and data scientists to seamlessly integrate AI-driven models into production data workflows. • Lead and mentor a team of 2 data engineers, fostering a culture of continuous improvement and technical excellence. • Set high standards for code quality, documentation, and rigorous peer reviews. • Oversee project execution, delegate responsibilities, and act as the technical point of escalation for complex data-related roadblocks. • Implement robust monitoring, alerting, and automated testing (Data Quality) to ensure the integrity of the data team's output. • Ensure data security and GDPR compliance across all international jurisdictions and workflows. • Identify opportunities to leverage new technologies or improve existing workflows to optimize data processing.

Role Description As a Sr Data Engineer, you will design and implement robust data architectures for enterprise platforms, including data lakes, warehouses, and lakehouse solutions. You will build scalable data pipelines, ensure data quality and reliability, and drive modernization initiatives. Collaborating closely with data science and analytics teams, you will deliver advanced data solutions while supporting compliance and governance requirements. This role offers opportunities to mentor junior engineers, evaluate emerging technologies, and contribute to technical excellence across the organization. Key Responsibilities - Design and implement data architecture for enterprise data platforms (data lakes, warehouses, lakehouse architectures). - Build scalable data pipelines using modern ETL/ELT frameworks (e.g., Airflow, DBT); ensure data quality, reliability, and performance. - Implement Change Data Capture (CDC) and real-time streaming solutions using technologies such as Kafka and Spark Streaming. - Optimize data infrastructure for performance and cost, including partitioning, compression, and caching strategies. - Establish data governance practices: data lineage, quality monitoring, schema management, and access controls. - Lead technical initiatives for data platform modernization; evaluate and adopt new technologies and tools. - Mentor junior data engineers, conduct code reviews, and establish best practices. - Collaborate with data science and analytics teams to deliver data solutions for advanced analytics. - Support compliance requirements for data security, privacy, and regulatory needs (e.g., GDPR, SOC2). Qualifications - 5+ years of data engineering experience building large-scale data platforms on cloud infrastructure. - Extensive experience with cloud data platforms: AWS (Redshift, Glue, EMR, S3), Azure (Synapse, Data Factory, ADLS), or GCP (BigQuery, Dataflow, GCS). - Expertise in SQL; proficiency in Python or Scala; experience with Spark for distributed data processing. - Hands-on experience with data pipeline orchestration tools (Airflow, DBT, Luigi, or similar). - Experience with streaming platforms (Kafka, Kinesis, Pub/Sub) and event-driven architectures. - Deep knowledge of relational databases (PostgreSQL, Oracle, SQL Server) and NoSQL databases (MongoDB, Cassandra, DynamoDB). - Strong skills in dimensional modeling, data normalization, and schema design. - Experience with Infrastructure as Code tools (Terraform, CloudFormation, or similar). - Bachelor’s degree in Computer Science, Engineering, or related field. - This position requires US Citizenship. Preferred Qualifications - Master’s degree in Computer Science, Engineering, or related field. - Experience with data compliance requirements (FedRAMP, ITAR, HIPAA). - Experience with lakehouse platforms (Databricks, Delta Lake). - Experience with CDC tools (GoldenGate, Debezium). - Oracle Cloud experience. Benefits - Healthcare benefits. - 401(k) plan and company match. - Paid vacation time and holidays. - Well-living programs. - Short-term and long-term disability coverage. - Basic life insurance. - Tuition reimbursement.