Scan your resume against ATS criteria for this Analytics Engineer (Position located in Bengaluru, India) role at KnowBe4.
KnowBe4 empowers the modern workforce to make smarter security decisions every day. Trusted by more than 70,000 organizations worldwide, KnowBe4 is the pioneer of digital workforce security, securing both AI agents and humans. The KnowBe4 Platform provides attack simulation and training, collaboration security, and agent security powered by AIDA (Artificial Intelligence Defense Agents) and a proprietary Risk Score. The platform leverages 15-years of behavioral data to combat advanced threats including social engineering, prompt injection, and shadow AI. By securing humans and agents, KnowBe4 leads the industry in workforce trust and defense.
Data Engineers work closely with business stakeholders to understand their goals and identify data-driven strategies to achieve those goals. They design data modeling processes, create algorithms and predictive models to extract the insight the business needs and help analyze the data to increase the productivity and efficiency of the business.
Partner with business stakeholders to translate reporting and analytics requirements into well-modeled, certified data definitions and BI-ready datasets.
Design, build, and maintain Snowflake Semantic Views — defining the tables, relationships, facts, dimensions, and metrics that form the governed, reusable definitions layer on top of the warehouse.
Author and curate verified queries, synonyms, and metric definitions so semantic views reliably power natural-language and AI-driven querying (e.g., Cortex Analyst / MCP-based access).
Use AI/LLM tools (e.g., Claude, Copilot, or similar) as part of the daily engineering workflow — for code generation, query drafting, documentation, and accelerating model development.
Own data quality, testing, and documentation for your models, and support the governance and certification of datasets and semantic views for broad self-service use.
Enable BI and downstream consumers (Looker/Tableau) by exposing consistent, trustworthy metrics through the modeled and semantic layers.Skills:
Strong dimensional and semantic data modeling skills — star schemas, facts vs. dimensions, grain, and slowly changing dimensions.
Production experience with Snowflake, including building or maintaining semantic views / semantic models (or a comparable semantic/metrics layer such as LookML, dbt Semantic Layer/MetricFlow, or Cube).
Ability to translate business metric definitions into governed, reusable data models and semantic objects.
Git-based version control and code review workflows for analytics code.
Strong SQL skills and hands-on Python experience for data transformation, testing, and tooling.
Practical, working knowledge of LLMs/generative AI — how they're prompted, their capabilities and limitations — and comfort using AI coding/analytics assistants as everyday tools.
We offer company-wide bonuses based on monthly sales targets, employee referral bonuses, adoption assistance, tuition reimbursement, certification reimbursement, and certification completion bonuses - all in a modern, high-tech, and fun work environment. For more details about our benefits in each office location, please visit www.knowbe4.com/careers/benefits
No recruitment agencies, please.
Partner with business stakeholders to translate reporting and analytics requirements into well-modeled, certified data definitions and BI-ready datasets.
Design, build, and maintain Snowflake Semantic Views — defining the tables, relationships, facts, dimensions, and metrics that form the governed, reusable definitions layer on top of the warehouse.
Author and curate verified queries, synonyms, and metric definitions so semantic views reliably power natural-language and AI-driven querying (e.g., Cortex Analyst / MCP-based access).
Use AI/LLM tools (e.g., Claude, Copilot, or similar) as part of the daily engineering workflow — for code generation, query drafting, documentation, and accelerating model development.
Own data quality, testing, and documentation for your models, and support the governance and certification of datasets and semantic views for broad self-service use.
Enable BI and downstream consumers (Looker/Tableau) by exposing consistent, trustworthy metrics through the modeled and semantic layers.Skills:**
Hands-on production experience building analytics models with dbt (staging/marts patterns, tests, documentation).
Strong dimensional and semantic data modeling skills — star schemas, facts vs. dimensions, grain, and slowly changing dimensions.
Production experience with Snowflake, including building or maintaining semantic views / semantic models (or a comparable semantic/metrics layer such as LookML, dbt Semantic Layer/MetricFlow, or Cube).
Ability to translate business metric definitions into governed, reusable data models and semantic objects.
Git-based version control and code review workflows for analytics code.
Strong SQL skills and hands-on Python experience for data transformation, testing, and tooling.
Practical, working knowledge of LLMs/generative AI — how they're prompted, their capabilities and limitations — and comfort using AI coding/analytics assistants as everyday tools.
We offer company-wide bonuses based on monthly sales targets, employee referral bonuses, adoption assistance, tuition reimbursement, certification reimbursement, and certification completion bonuses - all in a modern, high-tech, and fun work environment. For more details about our benefits in each office location, please visit www.knowbe4.com/careers/benefits
No recruitment agencies, please.
How to apply for Analytics Engineer (Position located in Bengaluru, India) at KnowBe4?
Click the "Apply on Company Website" button on this page to submit your application directly on the employer's official portal.
What is the salary for this role?
Salary details will be discussed during the interview.
What experience is required?
15-years of experience is required.
Is this position still open?
Yes, currently active and accepting applications.
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