Overview

The next part of your journey is right around the corner — with StanCorp Global Services

Responsibilities

• Ability to work on-site in Bengaluru, India is a requirement of the role. *
• Build and operate batch and streaming ingestion pipelines on Databricks (PySpark, Lakeflow/Delta Live Tables).
• Integrate event streams from Confluent Kafka into the Lakehouse and manage schema evolution.
• Build and operate Lakebase-backed operational data patterns alongside the lakehouse.
• Build ingestion and parsing pipelines for structured and unstructured content (documents, text) feeding the lakehouse, graph and vector stores.
• Operate and maintain Neo4j environments under established runbooks: backups and restores, monitoring, health checks and routine upgrades.
• Support vector index operations in Databricks Vector Search and Azure AI Search: run index refresh and sync pipelines and monitor retrieval data freshness.
• Execute disaster recovery procedures for platform data stores: backup/restore testing, failover drills and multi-region runbook execution.
• Implement lineage capture and freshness monitoring against published data contracts and SLAs.
• Automate data-quality and contract testing in CI/CD so violations fail fast, and respond to pipeline incidents.
• Maintain catalog and metadata hygiene in Unity Catalog, and contribute runbooks and operational documentation for the pipelines you own.

Qualifications

• Typically requires 4+ years of data engineering experience building production pipelines.
• Strong PySpark and SQL skills and solid Python fundamentals.
• Hands-on Databricks experience: Delta Lake, jobs/workflows and familiarity with Unity Catalog.
• Kafka/Confluent experience, including consuming event streams into analytical stores.
• Working knowledge of a graph or vector data store (Neo4j, Databricks Vector Search, Azure AI Search or equivalent), including routine operations such as backups, monitoring and index refreshes.
• Data-quality testing experience (Great Expectations, dbt tests or equivalent) and lineage/freshness monitoring.
• Git-based workflows and CI/CD for data pipelines
• Cypher basics and interest in growing into graph engineering.
• Disaster recovery or multi-region operations exposure (replication, failover drills, backup/restore testing).
• Lakebase or Postgres-style operational store experience.
• Confluent ecosystem depth (Schema Registry, connectors) and CDC tooling.
• Observability tooling (Datadog) and on-call experience.
• Good to have Databricks Data Engineer Associate or Confluent Certified Developer.
• Adaptability — Seeks information to understand the rationale for and importance of the change.
• Customer Focus — Displays an interest in the customer by trying to understand their concerns and issues; draws on customer insight to help others best meet current and future customer needs.
• Improvement Mindset — Demonstrates curiosity by asking questions regarding current approaches/methods and identifying potential changes.
• A rich benefits package that supports your health, well-being, and financial goals
• An annual incentive bonus plan tied to both individual and organizational performance
• Paid time off including earned leave, sick/casual leave, and public holidays, in accordance with the company’s leave policy
• A supportive, responsive management approach that empowers you to grow
• Opportunities for career advancement through learning, coaching, and leadership enablement
• A culture where your voice matters—your ideas shape our future, and we win as one
• Purpose-driven work that makes a difference for our customers, communities, and each other