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Popular mid-level data engineering role in Bangalore with broad tooling requirements increases competition.
Data engineering skills transfer well across industries, though telecom/OSS domain knowledge is advantageous.
Explicit 5+ years and mandatory cloud, warehouse, and pipeline tooling make filters stringent.
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Design, build, and operate batch and streaming data pipelines for centralized cloud data platform ingestion from OSS/BSS systems, network elements, and SaaS tools.
Model and curate data for analytics, reporting, network observability, and AI/ML use cases, including maintaining data warehouse/lakehouse on cloud (BigQuery/GCP, AWS).
Implement data quality, lineage, governance, and security measures; collaborate with multi-location teams to translate requirements into scalable solutions; establish engineering best practices and mentor juniors.
5+ years professional data engineering experience building production data pipelines and platforms.
Strong SQL and at least one programming language for data (Python preferred; Scala/Java acceptable).
Experience with cloud data warehouse/lakehouse (BigQuery strongly preferred; Snowflake/Redshift/Databricks comparable).
Onsite 3 days/week in Bangalore, India (location requirement explicitly mentioned).
Experienced with telecom OSS/BSS, network data, or related domains to effectively handle CRM, billing, mediation, and network KPI data.
Proficient operating on major cloud platforms with knowledge of IAM, cost optimization, security, and data privacy compliance measures.
Capable of working across distributed global teams and ready to take high ownership in building enterprise data engineering foundations in a startup-to-growth environment.