This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description Bowhead seeks a Data Engineer to join our team in Mobile, AL. The Data Engineer will not only build scalable data pipelines, but also help operate and secure our cloud environment. This role blends data engineering, cloud platform administration, and cyber compliance to ensure our data platforms are reliable, auditable, and compliant with federal security standards. This position is fully remote. Responsibilities - Data Engineering - Design, build, and maintain ETL/ELT pipelines for batch and streaming workloads. - Develop data processing and automation solutions in Python. - Write and optimize SQL for transformations, data modeling, and performance tuning. - Build and manage real-time data ingestion using message brokers and stream processing frameworks. - Inventory and catalog data assets — tracking lineage, classification, and ownership to support governance and compliance. - Troubleshoot data quality, pipeline, and performance issues across the platform. - Platform Operations - Administer and support cloud resources including identity, networking, storage, and compute. - Implement and maintain CI/CD pipelines for data workloads and infrastructure deployments. - Configure and manage infrastructure using IaC and GitOps practices. - Containerize and deploy workloads using Docker and Kubernetes. - Monitor system health, performance, and reliability; respond to incidents and outages. - Automate workflows across data pipelines, infrastructure provisioning, and operational processes. - Manage access controls, backups, logging, patching, and environment hardening. - Cyber Compliance - Implement and maintain security controls including logging, encryption, IAM, and configuration baselines aligned to NIST 800-53. - Support FedRAMP/FISMA compliance activities including control implementation, evidence collection, POA&M tracking, and audit preparation. - Work with security and governance teams to ensure environments meet required federal standards. - Assist with vulnerability management, remediation, and security documentation. Qualifications - BA/S in relevant technical field preferred. Years of experience may substitute in education requirement. - Five (5+) years of relevant technical experience. - Proficiency in Python for data processing and automation. - Strong SQL skills across relational and non-relational databases. - Experience with distributed data processing frameworks (e.g., Spark) including streaming workloads. - Familiarity with message brokers and event-driven ingestion patterns. - Experience with data cataloging and inventory for governance and compliance. - Production cloud experience (Azure preferred). - Experience with Docker, Kubernetes, CI/CD pipelines, and IaC/GitOps practices. - Ability to design scalable solutions and troubleshoot complex data and system issues. - Experience supporting security and compliance in cloud environments — controls implementation, logging, IAM, encryption, and audit support aligned to NIST 800-53 or equivalent frameworks. Nice to Have - Experience with Databricks, Delta Lake, or lakehouse architectures. - Familiarity with cloud-native governance and security tooling. - Experience with Terraform, Bicep, or similar IaC tools. - Prior experience supporting FedRAMP or FISMA authorization processes. - Experience with agentic coding tools and AI-assisted development workflows. - Experience with Navigation data and GIS. Tech Stack - Python - SQL - Spark (batch & streaming) - Message Brokers - Docker - Kubernetes - CI/CD - IaC/GitOps - Cloud Platforms (Azure preferred) - Data Lakehouse - NIST 800-53 / FedRAMP Physical Demands - Must be able to lift up to 25 pounds. - Must be able to stand and walk for prolonged amounts of time. - Must be able to twist, bend and squat periodically. Security Clearance Must be able to obtain a security clearance at the Public Trust level. US Citizenship is a requirement for Secret clearance at this location.

• Lead the architecture and development of streaming data pipelines that deliver market and operational data to pricing algorithms with sub-second latency, relying on technologies such as Kafka and Flink • Define architectural standards for real-time data delivery, reliability, and observability • Ensure production SLAs are met for systems that directly impact pricing and trading workflows • Collaborate with quantitative researchers, data scientists, and engineers to deliver reliable data inputs for modeling and backtesting • Mentor engineers on best practices for distributed data systems and production-grade data pipelines • Contribute to the broader data platform, including batch pipelines and data modeling workflows when needed

• Evaluate and optimize the reporting layer of our Snowflake data warehouse to enhance cost efficiency and compute utilization. • Develop and implement strategies to improve query performance, reduce data processing time, and enhance overall efficiency. • Collaborate closely with the data engineering team to implement optimizations without compromising data integrity or security. • Utilize advanced analytic engineering techniques within Snowflake to optimize data transformations and computations. • Design efficient data models and schemas to support optimized reporting and analytics. • Implement best practices for data loading, storage, and retrieval to minimize costs and maximize performance. • Optimize query performance by tuning Snowflake configurations and query execution plans. • Implement caching strategies and materialized views to improve response times for commonly used reports. • Collaborate with data engineers to ensure efficient ETL processes and data transformations.

• Build ELT pipelines using BigQuery OR Snowflake, dbt, and cloud services • Write production-grade Python code for ingestion, transformation, and automation • Design analytics-ready data models • Work directly with customers to gather and clarify requirements • Ensure data quality via testing, validation, and monitoring • Debug pipeline failures, data issues, and performance bottlenecks • Participate in code reviews and follow engineering best practices • Work with 3–5 hours overlap with US EST/CST/PST