Principal Data Engineer

RS21

10h

About The Position

The Principal Data Engineer is a senior practitioner leader who operates at the intersection of hands-on technical execution, enterprise architecture, client-facing solutioning, and cross-functional program leadership. This role is designed for an engineer who can walk into any project environment, immediately understand what needs to be built and why, sequence the work, align the teams, and deliver. At the Principal level, this person drives data platform strategy for the organization, not just a single project. They set engineering standards, evaluate platform and orchestration trade-offs, lead reference architecture decisions across engagements, and are the person RS21 turns to when a technical decision is hard. They translate ambiguous client requirements into scalable architectures, own the full data engineering lifecycle from ingestion through AI enablement, and bridge the communication gap between business stakeholders, product teams, platform engineers, and data scientists with equal fluency. This role further serves as an embedded technical program lead, with the discipline to decompose ambiguous initiatives into structured, sequenced delivery work, the systems thinking to connect every technical task to its business outcome, and the ownership to keep multi-workstream programs on track independently. Critically, the Principal Data Engineer is a force multiplier. They raise the capabilities of those around them, train and coach junior and mid-level staff, establish the patterns and practices RS21's data engineering function grows from, and actively contribute to RS21's business development and proposal efforts as a credible technical voice.

Requirements

Bachelor's degree or equivalent experience in data engineering, computer science, or a related field.
7+ years of hands-on data engineering experience, with at least 3 years in a senior, lead, or architect-level capacity.
Deep, hands-on experience with AWS data services such as S3, Glue, Glue Catalog, Lake Formation, Redshift, Athena, EMR, Kinesis, MSK/Kafka, Lambda, Step Functions, and EventBridge.
Proven ability to design and deliver production-grade ETL/ELT pipelines, data warehousing solutions, and streaming architectures at scale.
Demonstrated experience supporting LLM, AI, or machine learning data workflows, including data preprocessing, embedding pipelines, and vector store integration (Amazon OpenSearch, Bedrock, or equivalent).
Track record of client-facing work: requirements gathering, stakeholder communication, and translating business needs into scalable technical solutions.
Experience functioning as a technical program lead owning delivery plans, managing Jira-based project tracking, and coordinating cross-functional technical teams.
Strong architectural reasoning and systems thinking, able to hold the full picture while executing in the details.
Excellent written and verbal communication skills with demonstrated ability to adapt technical depth to audience.

Nice To Haves

AWS certifications: Solutions Architect – Professional, Data Engineer – Associate (DEA-C01), or ML Engineer
Databricks Certified Data Engineer (Associate or Professional) and/or dbt Certified Developer.
Experience with infrastructure-as-code tools (Terraform, CDK, or similar) and DataOps/DevOps practices.
Background in consulting, professional services, or multi-client delivery environments.
Familiarity with data governance frameworks, data cataloging, and enterprise lineage tooling.
Experience with Databricks (Delta Lake, MLflow), dbt, and Airflow/Prefect orchestration.
Exposure to DoD, federal, or regulated-sector data environments; FedRAMP-compliant architecture experience a plus.

Responsibilities

Drive RS21's data platform strategy, evaluate orchestration tools, pipeline frameworks, and storage architectures across engagements and make organization-wide recommendations.
Design, build, and maintain production-grade, scalable data pipelines supporting batch and real-time ingestion, transformation, and delivery.
Architect production-grade ETL/ELT workflows with data quality controls, lineage tracking, monitoring, and observability built into the design from day one.
Establish data contracts, pipeline standards, and engineering norms that apply across RS21's project portfolio.
Ensure data reliability, performance, and scalability across platforms, and hold teams accountable to those standards.
Evaluate and select foundation model strategies for RS21's AI and LLM-powered offerings; guide ethical AI approach across engagements.
Design and implement data pipelines that support LLM and AI use cases, including: Document and unstructured data ingestion, Data preprocessing, enrichment, and embedding generation, Vector store architecture and retrieval-optimized data structures.
Lead architecture decisions; drive RAG and vector search platform strategy across projects.
Ensure data freshness, lineage, and governance for AI-powered systems.
Optimize data structures and retrieval patterns to support efficient LLM context usage.
Set RS21's cloud data strategy, evaluate multi-cloud trade-offs, drive AWS platform decisions, and contribute to reusable reference architectures for data lakes, warehouses, streaming systems, and AI-ready platforms.
Architect and provision AWS services to support data and AI workloads across S3, Redshift, Glue, Lake Formation, Athena, EMR, Kinesis, MSK, Lambda, and Step Functions.
Lead Lake Formation architecture, fine-grained access controls, and data governance design.
Partner with platform and DevOps teams to ensure secure, cost-effective, and scalable cloud deployments.
Drive infrastructure-as-code and automation practices; lead DevOps reliability strategy for data platforms.
Lead discovery and requirements-gathering engagements with clients to translate ambiguous business and operational needs into concrete, scalable data and AI architectures.
Serve as RS21's primary technical face in client-facing data settings, capable of presenting to executive stakeholders and engineering teams in the language each audience needs.
Produce reference architectures, solution design documents, and technical roadmaps that guide both client delivery and internal product development.
Assess and document client data readiness for analytics, AI, and LLM adoption; identify gaps and prescribe actionable remediation paths.
Own the technical narrative during solutioning, from pre-sales and scoping through delivery kickoff and handoff.
Own end-to-end technical execution planning for data engineering workstreams. Define the sequence of work, identify dependencies, and ensure delivery milestones map to both technical and business outcomes.
Operate as a technical program lead within project delivery: decompose complex initiatives into structured Jira epics, stories, and tasks with clear acceptance criteria; understand how every ticket fits into the larger program arc.
Establish and continuously improve RS21's delivery standards for data engineering programs, translating lessons learned across engagements into stronger project management practices organization wide.
Partner with project managers and product owners to ensure the technical execution plan stays aligned with contractual, operational, and business constraints.
Lead planning, estimation, and review ceremonies with the technical authority to drive hard decisions to resolution when they arise.
Serve as the central coordination point between client stakeholders, product teams, platform engineers, ML/data science teams, and DevOps, translating across all languages with fluency.
Support the evolving data architecture behind RS21's product and AI capabilities, including predictive and real-time ML systems.
Assess and improve internal and client data readiness for analytics and AI adoption.
Serve as the connective tissue across client stakeholders, product, platform engineering, ML and data science, and DevOps teams, moving fluidly between business language and technical depth depending on who is in the room.
Shape RS21's data engineering talent strategy, anticipate capability gaps before they become program risks, and partner with technical leadership on the hiring, development, and structural decisions needed to close them.
Train, mentor, and grow junior and mid-level data engineers in both technical depth and architectural thinking.
Build the onboarding frameworks, internal playbooks, and knowledge-transfer practices that make RS21's data engineering capability portable, consistent, and independent of any single person.
Conduct code reviews, architecture reviews, and design critiques that elevate team output quality and raise the floor of what RS21 ships.
Model big-picture thinking, help the team understand not just what to build, but why it matters and how it connects to client outcomes and RS21's broader technical strategy.
Collaborate closely with developers building LLM features to ensure data pipelines meet AI requirements.
Shapes how RS21 communicates with data, influences clients and executives through evidence-based, decision-driving narratives.
Holds the full system in view across the organization, client, and market; shapes decisions with long-horizon thinking.
Document data architectures, pipelines, and best practices to support transparency and reuse.
Contributes to RS21 business development, proposal efforts, and technical volume authorship as a credible senior voice.