Senior Big Data Engineer
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Requirements
• Minimum 5 years of experience working with large-scale big data platforms and distributed systems. • Strong experience with cloud data technologies such as Cosmos (MapReducer), Spark, HDI, and ADLS Gen2. • Minimum 5 years of hands-on experience with SQL and at least one high-level programming language (C#, Scala, Java, or Python). • Minimum 5 years of experience with CI/CD pipelines, debugging, monitoring, and engineering lifecycle practices. • Proven ability to troubleshoot complex production issues and deliver reliable solutions. • Experience working in high-reliability data engineering environments. • Ability to work independently in a high-execution, fast-paced environment. • Experience following security, governance, and compliance standards in production systems. • Experience working on large-scale telemetry or data processing platforms. • Prior experience in security remediation, secret rotation, endpoint hardening, and compliance-driven engineering. • Hands-on experience with data governance, access control, and data partitioning strategies. • Experience maintaining and improving production pipelines across cloud data platforms. • Background in high-volume, high-throughput distributed systems. • Familiarity with enterprise engineering processes, internal tooling, and secure deployment environments. • Ability to ramp up quickly and immediately contribute to independent execution work.
Responsibilities
• In this role, you will work closely with senior engineers and an engineering manager to design, develop, validate, and deploy features across large-scale data platforms. You will be responsible for executing high-priority engineering tasks, addressing security and governance requirements, and maintaining reliable data pipelines. The work is highly execution-focused, with an emphasis on fast ramp-up, independent ownership, and delivering production-ready solutions that meet strict security, compliance, and reliability standards. You will operate within established engineering practices, follow deployment rules, and collaborate with full-time engineers who will support onboarding and accelerate your ramp-up. Access to secure environments (pre-production and production) will be required as part of this role. • Design, develop, test, and deploy features across distributed data platforms. • Maintain and enhance data pipelines running on big data and cloud data technologies. • Perform security-related engineering work, including fixing code vulnerabilities, updating secrets and identities, and ensuring secure endpoints. • Implement governance and compliance updates, including data partitioning, access controls, and physical access restrictions. • Write, modify, debug, and troubleshoot production code and services. • Follow standard engineering lifecycle practices, including CI/CD, monitoring, and deployment workflows. • Execute tasks independently with minimal oversight and deliver high-priority items on aggressive timelines. • Collaborate with engineers to ramp up quickly and take ownership of execution work. • Operate within secure environments and follow all access, security, and compliance requirements.
Benefits
• At Blueprint, we strive to offer competitive pay that reflects the value of our team members. Compensation for this role is influenced by a variety of factors, including skills, education, responsibilities, experience, and geographic market. For candidates based in Washington State, California and other states the anticipated salary range is $48.08 to $57.69 Hourly. Please note that we typically do not hire new employees at the top of the posted range. Actual starting pay will be determined based on experience, skills, and internal equity. The final salary and job title may vary depending on the selected candidate’s qualifications and could fall outside the stated range. • $48.08 to $57.69 Hourly