Senior Data Engineer Python, Databases, Cloud & GenA
Location: Phoenix, AZ – 3 Days onsite
Experience Hybrid, 3 days per week on-site
Core Technologies 8-12+ years Python, SQL, Google Cloud Platform, AWS, Oracle, PostgreSQL, Couchbase, GenAI, Agentic AI, LLMs, RAG About the Role We are looking for a hands-on Data Engineer with expert Python skills, deep database expertise (Oracle, PostgreSQL, Couchbase), and cloud experience on Google Cloud Platform and AWS. You will modernize and build scalable, high-performance data platforms, including AI-powered solutions using LLMs, RAG, and agentic frameworks. You will work across the full engineering lifecycle: architecture, design, coding, performance tuning, deployment, and production support. What You'll Do Python Engineering
- Build production-grade Python applications, backend services, and reusable components using clean code, SOLID principles, and design patterns
- Develop ETL/ELT frameworks, ingestion services, validation utilities, and workflow automation
- Build REST APIs and microservices with FastAPI, Flask, or similar
- Apply async, multithreading, and multiprocessing to optimize high-volume workloads
- Build database integration layers (connection pooling, bulk processing, transaction management)
- Create tooling for database migration, schema comparison, data reconciliation, data quality, and performance monitoring
- Own testing (unit, integration, mocking), CI/CD pipelines, code reviews, and production troubleshooting Database Architecture & Optimization
- Design scalable, secure relational and NoSQL data models, indexing, and partitioning strategies
- Write and tune complex SQL, stored procedures, functions, and views, including execution plan analysis
- Apply knowledge of database internals: concurrency, locking, isolation levels, storage
- Design replication, HA, backup, recovery, and DR solutions
- Lead modernization work, including Oracle-to-PostgreSQL and on-prem-to-cloud migrations
- Ensure data integrity, security, and governance Cloud Engineering (Google Cloud Platform & AWS)
- Build and deploy cloud-native data solutions and serverless, event-driven Python applications
- Work with services such as BigQuery, Cloud SQL, AlloyDB, Dataflow, Pub/Sub, Cloud Run, Vertex AI, RDS, Aurora, S3, Redshift, Glue, Lambda, Step Functions, and Bedrock
- Automate infrastructure and deployments; implement monitoring and logging
- Apply cloud security best practices (IAM, encryption, secrets management, network controls)
- Optimize cloud performance and cost across hybrid and multi-cloud environments Data Pipelines
- Design batch, near-real-time, and streaming pipelines using Python, SQL, and cloud-native services
- Integrate data across Oracle, PostgreSQL, Couchbase, cloud databases, APIs, and object storage
- Implement data quality checks, schema validation, audit logging, and automated recovery
- Work with Spark, Airflow, Kafka, and cloud orchestration tools
- Build observability and lineage to support analytics, operational, and AI/ML use cases GenAI & Agentic AI
- Build and deploy production AI applications and agents using Python and LLMs
- Develop single- and multi-agent systems (planning, tool calling, multi-step orchestration) with LangChain, LangGraph, CrewAI, AutoGen, or similar
- Design RAG architectures: ingestion, chunking, embeddings, vector indexing, hybrid retrieval, reranking, and context optimization
- Work with OpenAI APIs, Vertex AI/Gemini, and AWS Bedrock
- Use vector databases such as pgvector, Pinecone, FAISS, or Chroma
- Build agents that securely interact with Oracle, PostgreSQL, Couchbase, and cloud data platforms
- Develop reusable Python frameworks for LLM orchestration Required Qualifications
- 8-12+ years in data engineering or software engineering
- Expert Python (OOP, decorators, generators, context managers, async) plus Pandas, NumPy, SQLAlchemy, psycopg, python-oracledb, PyTest, boto3, and Google Cloud SDKs
- Deep hands-on experience with Oracle and PostgreSQL, including performance tuning
- Hands-on Google Cloud Platform and AWS data engineering experience
- Experience building and deploying LLM/RAG-based applications Preferred Qualifications
- Couchbase experience
- Oracle-to-PostgreSQL migration experience
- Spark, Airflow, Kafka
- Multi-agent framework experience (LangGraph, CrewAI, AutoGen)
