Senior Software Engineer - Data Platform

What you'll do:

As a Senior Software & Data Engineer you will own the architecture and code that powers every data-driven decision behind our aircraft design, manufacturing, flight-test and fleet-health operations.

• Architect, design and hands-on code distributed data services (micro-services, APIs, SDKs) in Python, Java or Scala.
• Lead the end-to-end build-out of our lakehouse-style warehouse (Parquet / Iceberg / Trino) and its streaming ingestion fabric (Kafka / Spark Structured Streaming / Flink).
• Optimize large-scale ETL/ELT and feature pipelines for time-series & telemetry (vehicle CAN, sensor logs, flight-test data) reaching tens of billions of rows per day.
• Embed GenAI & LLM workflows (vector search, RAG, agentic orchestration, LLM-powered data quality/metadata enrichment) directly into pipelines and user-facing tools.
• Champion Kubernetes-native CI/CD, observability and cost-efficient autoscaling for all data services.
• Define and enforce best-in-class data governance, lineage and security (IAM, fine-grained access, encryption).
• Partner with Data Science, Flight-Test and Manufacturing teams to turn raw data into predictive maintenance, anomaly-detection and root-cause analysis products.
• Mentor mid-level engineers, perform design reviews, and set engineering standards across the org

What you need:

• 7+ years building production-grade data or platform software at scale.
• BS/MS in Computer Science, Data Engineering, Software Engineering or related field.
• Deep mastery of software architecture & design patterns for distributed systems.
• Expert-level coding in Python plus one of Java / Scala; strong command of testing, profiling and performance tuning.
• Hands-on expertise with:
• Streaming & Batch: Kafka, Spark / PySpark, Flink, Airflow.
• Storage & Query: Parquet, Iceberg or Delta, Trino / Presto, lakehouse & warehouse paradigms.
• Cloud & Containerization: AWS (EKS, S3, Glue, Redshift, EMR), Kubernetes, Helm, Terraform.
• Parallel / distributed compute and high-throughput, low-latency data services.
• CI/CD & Observability: GitHub Actions, ArgoCD, Prometheus, Grafana, Datadog.
• Proven track record in automotive / aerospace, telemetry, signal-processing or other time-series-heavy domains.
• Demonstrated ability to apply GenAI / LLM tooling (OpenAI, Hugging Face, LangChain, vector DBs) to real-world data products and developer workflows.
• Excellent communication; enjoy collaborating across mechanical, flight-test, manufacturing and software disciplines.

Bonus Requirements:

• Experience deploying ML models or MLOps pipelines to edge devices or embedded compute units.
• Contributions to open-source data infrastructure projects.

Please note that this job description is intended to provide a general overview of the position and does not include an exhaustive list of responsibilities and qualifications

At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company's business strategy. For this position we are targeting a base pay between $134,000 - $180,000. Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.

Archer is committed to working with and providing reasonable accommodations to job applicants with physical or mental disabilities, and those with sincerely held religious beliefs. Applicants who may require reasonable accommodation for any part of the application or hiring process should provide their name and contact information to Archer's People Team at people@archer.com. Reasonable accommodations will be determined on a case-by-case basis.