Python Developer , Data Engineer

Python Developer Data Engineering

Experience: 6 to 10 Years
Location: Remote
Employment Type: Contract

Role Overview

We are seeking an experienced Python Developer with strong data engineering expertise to build and operate the ingestion and transformation backbone of the Insights Hub platform. The role involves processing interaction data and call recordings from NICE CXone, managing transcription and PII redaction, normalizing data into relational models, and building vector collections for AI and RAG workloads.

Key Responsibilities

• Build scalable Python ETL pipelines to ingest recordings and interaction metadata from NICE CXone APIs.
• Develop batch and incremental data-processing workflows with appropriate concurrency, pagination, retry, and rate-limit handling.
• Transform raw payloads into normalized relational data models.
• Integrate Vertex AI Speech-to-Text, including diarization, channel configuration, and confidence scoring.
• Implement PII detection, masking, and de-identification using Google Cloud Sensitive Data Protection.
• Build embedding pipelines and populate Qdrant vector collections using dense and sparse vectors.
• Implement hybrid retrieval with reciprocal rank fusion and optimize HNSW parameters.
• Develop Airflow/Cloud Composer DAGs with retry, backfill, idempotency, monitoring, and alerting.
• Build internal APIs using FastAPI or similar frameworks.
• Monitor pipeline throughput, latency, failures, and data freshness.
• Write unit and integration tests, review code, resolve production incidents, and maintain technical documentation.

Required Skills

• Strong production experience with Python 3.10+, pandas, SQLAlchemy, async I/O, packaging, and pytest.
• Proven experience building large-scale batch and incremental ETL pipelines.
• Advanced SQL with BigQuery and PostgreSQL, Cloud SQL, or SQL Server.
• Airflow or Google Cloud Composer.
• GCP services, including Cloud Run, Cloud Storage, IAM, service accounts, and Secret Manager.
• REST API integrations using OAuth 2.0, pagination, rate limiting, retries, and backoff.
• Docker, CI/CD pipelines, and Git-based development workflows.

Preferred Skills

• Vector databases such as Qdrant, Pinecone, Weaviate, or pgvector.
• Embedding models and dense/sparse hybrid retrieval.
• Speech-to-text or audio-processing pipelines.
• NICE CXone, Genesys, Five9, or Amazon Connect.
• Data privacy controls, DLP, masking, and tokenization.
• Financial services or contact-center domain experience.
• Terraform or similar infrastructure-as-code tools.

Success in the First 90 Days

• Independently own an end-to-end pipeline from NICE CXone extraction through vector-store population.
• Reduce pipeline failures and improve data freshness against established SLAs.
• Deliver production-ready documentation for all owned components.