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Salary
$31k – $61k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Senior · 6+ years exp
Overview
Company
Impact
Profile match
PurpleSphere is an AI-powered B2B SaaS platform that enhances physical security and facility management through real-time threat analysis, machine learning, generative AI, and mobile credential solutions.

Responsibilities:

  • Own the complete medallion architecture Bronze Silver Gold pipeline: land raw events (object storage), clean, conform and dedupe them (Silver), and model curated aggregates (Gold).
  • Design the multi-tenant data model: data partitioned and isolated per tenant and per facility, with row-level tenancy and ensure that isolation holds across every layer.
  • Author and operate Airflow DAGs for both incremental ingestion and historical backfill.
  • Build and support the streaming ingestion path: API polling Kafka consumer Bronze and pair with the junior engineer who owns it.
  • Build real-time / stream processing on top of the ingestion path: low-latency transformations, event-time windowing and aggregations over Kafka streams to power near-real-time analytics.
  • Make pragmatic design decisions and document the patterns clearly for the team.

Requirements:

  • 6+ years in data engineering, with senior-level ownership of production pipelines.
  • Strong Python for data work.
  • Hands-on Airflow with DAG authoring, dependencies, and backfills.
  • Solid PostgreSQL: schema/data modelling and query performance.
  • Experience with medallion / layered ELT patterns (raw, cleaned, curated).
  • Comfortable with S3 / object storage and partitioning strategies.
  • Working knowledge of Kafka consumers.
  • Hands-on stream processing with Apache Flink (or similar) event-time semantics, windowing, and stateful streaming for real-time pipelines.
  • Experience with a data lake/lakehouse (e. g. Delta Lake, Apache Iceberg) or a cloud data warehouse (e. g. Snowflake, BigQuery, Redshift).
  • A real data-quality and reconciliation mindset you validate, you don't assume.
  • Very good at problem solving.
  • Tech stack: Python, Apache Airflow, Apache Flink, Apache Kafka, PostgreSQL, S3 / object storage, data lake/lakehouse (Delta Lake, Apache Iceberg), cloud data warehouse (Snowflake / BigQuery / Redshift), medallion / ELT architecture.

Nice to have:

  • Multi-tenant data modelling and tenant-isolation experience.
  • dbt or similar transformation tooling.
  • Awareness of data-governance / GDPR-readiness.
  • Experience mentoring junior engineers.
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