
Principal Software Architect
1 day ago
About Role:
We are seeking an experienced High-Performance Python Engineer to lead our architecture and engineering teams.
- Job Type: Full-Time Employment
Responsibilities:
- Architecture and Reuse:
- Design and build a shared component library for data pipelines, ingestion, parsing, extraction, validation, enrichment, and publishing.
- Define patterns and templates for Apache Beam pipelines and Databricks jobs; standardize configuration, packaging, versioning, CI/CD, and documentation.
- Create pluggable interfaces for multiple teams to swap extractors, OCR providers, and EMR publishers without code rewrites.
- Define a repository strategy for each use case.
- Performance and Reliability:
- Own end-to-end profiling and tuning of data services: cProfile, memory analysis, CPU vs I/O performance metrics.
- Instrument services with Elastic APM and correlate traces/metrics with Splunk logs; build dashboards and runbooks.
- Implement concurrency best practices: asyncio for I/O-bound tasks, ThreadPool/ProcessPool for CPU-bound tasks, batching, rate limiting, retries, etc.
- Implement robust API rate limiting/governance: enforce provider TPM and concurrency caps, request queueing/token budgeting, and emit APM/Splunk metrics (throttle rate, queue depth, cost per job) with alerts.
- Establish service-level objectives (SLOs)/alerts for throughput, latency, error rates; set up dead-letter queues (DLQs) and recovery patterns.
- Team Enablement:
- Mentor developers, lead design reviews, codify best practices, write clear documentation and examples.
- Partner with machine learning engineers on the future LLM/SLM path (evaluation harness, safety/PII, cost/perf).
Requirements:
- 7+ years Python with strong experience in performance, concurrency (asyncio, concurrent.futures, multiprocessing), profiling, and memory tuning.
- Observability expertise: Elastic APM instrumentation and dashboarding; Splunk for logs and correlation; OpenTelemetry familiarity.
- Must have implemented large-scale data pipelines with Apache Beam and/or Spark, including hands-on Databricks experience (Jobs, Delta Lake, cluster tuning).
- Document processing: OCR (Tesseract, AWS Textract, Azure Form Recognizer), PDF parsing, text normalization.
- Cloud and tooling: AWS/Azure/GCP, Dataflow/Flink, Terraform, Docker; cost/performance tuning on Databricks.
- Security/compliance mindset (HIPAA), secrets management, least-privilege access.
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