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Bangalore metro, popular data-engineer role, and broad tooling requirements create moderate competition.
Core data engineering skills transfer across industries, though IoT/telematics/video domain preference increases specificity moderately.
Explicit 10+ years requirement plus specific cloud, warehouse, and tooling experience enforces stringent screening.
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Define and drive technical strategy for Lytx's cloud data warehouse and lakehouse platform optimizing performance, cost, and reliability at scale.
Design scalable data models, pipelines, and storage layers supporting analytics, reporting, and machine learning.
Lead cross-team technical projects, improve data quality and governance, and elevate engineering practices through mentorship and architecture influence.
10+ years experience in data engineering with large-scale cloud data warehouse or lakehouse platform management in production.
Hands-on expertise with cloud data warehouses (Snowflake, BigQuery, Redshift) and distributed data processing tools (e.g., Spark).
Proficient in SQL, Python, and data pipeline orchestration tools (e.g., dbt, Airflow).
Experience managing data infrastructure on major cloud providers (AWS, Azure, GCP).
Proven ability to lead technical, multi-team initiatives and influence architectural decisions without direct authority.
Strong understanding of data modeling, warehouse design patterns, and balance between batch and streaming data architectures.
Experienced in pragmatic engineering decisions, balancing scale with simplicity, and clear communication across technical and business stakeholders.