Data Engineer - Sr. Consultant

• Lead architecture and delivery of large‑scale data platforms (ingestion, transformation, storage, metadata, lineage, quality, governed access)

• Design high‑volume batch and streaming pipelines (Spark/Flink/Kafka) with clear SLAs/SLOs, observability, and cost/performance targets for global transaction processing.

• Build and harden back‑end services and APIs (REST/gRPC authN/Z, rate limiting, quotas, resilience patterns) that power data products and model operations on Kubernetes.

• Partner with Product Team to translate requirements into secure, robust solutions be the team’s technical representative across forums and stakeholders.

• Drive proofs of concept to de‑risk tech choices quickly prototype, then lead or hand off for productionization with best practices.

• Champion engineering standards- CI/CD, TDD, data contracts, catalog/governance, PII handling, RBAC/ABAC, audit, retention.

• Establish domain‑oriented data models (warehouse/lakehouse/data mesh) and semantic layers enabling analytics

• Own reliability for pipelines and services: metrics, incident response, capacity planning, continuous improvement

• Mentor senior engineers and onboard new joiners foster mutual accountability and effective cross‑time‑zone collaboration.

• GenAI enablement- build/enhance RAG pipelines architect/optimize AI agents for planning/reasoning/acting integrate MCP tools/clients leverage LangChain/LangGraph contribute to prompt design and fine‑tuning.

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.