Smartsheet
About this role
Smartsheet makes work management software and is now wiring AI agents into it, and this seat owns the
analytics layer underneath. You lead the architecture and implementation of the transformation systems
inside Snowflake that turn a raw data lake into clean, documented data products for data science,
analytics and reporting. The modelling approach is named and specific: Data Vault 2.0, AutomateDV,
dbt core, Airflow, Snowflake, GitLab and SQL. You also build the frameworks that catch data quality
problems early and write the testing plans that validate them, then push data out to the platforms
the business actually works in. Apply if you are an analytics engineer who thinks in models and
contracts rather than dashboards, and who wants ownership of the warehouse rather than a seat in the
queue for it.
analytics layer underneath. You lead the architecture and implementation of the transformation systems
inside Snowflake that turn a raw data lake into clean, documented data products for data science,
analytics and reporting. The modelling approach is named and specific: Data Vault 2.0, AutomateDV,
dbt core, Airflow, Snowflake, GitLab and SQL. You also build the frameworks that catch data quality
problems early and write the testing plans that validate them, then push data out to the platforms
the business actually works in. Apply if you are an analytics engineer who thinks in models and
contracts rather than dashboards, and who wants ownership of the warehouse rather than a seat in the
queue for it.
Who this is for
Requirements. 6+ years of experience in advanced data modelling using Data Vault (DV 2.0). Proven
experience building analytics systems with data transformation, dependency and workload management,
with the toolset named as Data Vault, AutomateDV, dbt core, Airflow, Snowflake, GitLab and SQL.
Proven experience building and maintaining business analytics layers and semantic layers that let
non-technical users self serve.
What you would do. Lead the implementation of efficient and scalable systems that optimise data
transformations from the Snowflake data lake into clean, documented data products. Contribute to
design standards and architectural principles. Build and maintain a governed, robust, reliable and
scalable analytics system (DW/DV). Work with BI analysts and data scientists on data accessibility
guidelines. Drive data democratisation by activating data on platforms including the Smartsheet
platform itself, Amplitude, Thoughtspot and Gainsight. Create frameworks that improve data quality
and observability so issues are found faster. Create and implement data testing plans covering data
validation, data quality assessment and regression testing to catch anomalies.
Reporting line and location, both stated. "This full-time position reports to the Director of
Analytics Engineering and is based in Smartsheet's corporate offices in Bengaluru, India." The job
title itself says Hybrid, Bangalore.
⛔ A remote tag to ignore. This posting carries an #LI-Remote tag while its own title says "Hybrid,
Bangalore" and its body says it is based in the Bengaluru offices. Every Smartsheet India posting in
this edition carries that same contradiction. The body wins: this is a Bengaluru hybrid job.
Who this is for. An analytics engineer with six or more years who has actually built with Data Vault,
because that is the first requirement and it is specific enough that adjacent modelling experience
will show. If you know dbt and Snowflake but have never done DV 2.0, expect that to come up early.
experience building analytics systems with data transformation, dependency and workload management,
with the toolset named as Data Vault, AutomateDV, dbt core, Airflow, Snowflake, GitLab and SQL.
Proven experience building and maintaining business analytics layers and semantic layers that let
non-technical users self serve.
What you would do. Lead the implementation of efficient and scalable systems that optimise data
transformations from the Snowflake data lake into clean, documented data products. Contribute to
design standards and architectural principles. Build and maintain a governed, robust, reliable and
scalable analytics system (DW/DV). Work with BI analysts and data scientists on data accessibility
guidelines. Drive data democratisation by activating data on platforms including the Smartsheet
platform itself, Amplitude, Thoughtspot and Gainsight. Create frameworks that improve data quality
and observability so issues are found faster. Create and implement data testing plans covering data
validation, data quality assessment and regression testing to catch anomalies.
Reporting line and location, both stated. "This full-time position reports to the Director of
Analytics Engineering and is based in Smartsheet's corporate offices in Bengaluru, India." The job
title itself says Hybrid, Bangalore.
⛔ A remote tag to ignore. This posting carries an #LI-Remote tag while its own title says "Hybrid,
Bangalore" and its body says it is based in the Bengaluru offices. Every Smartsheet India posting in
this edition carries that same contradiction. The body wins: this is a Bengaluru hybrid job.
Who this is for. An analytics engineer with six or more years who has actually built with Data Vault,
because that is the first requirement and it is specific enough that adjacent modelling experience
will show. If you know dbt and Snowflake but have never done DV 2.0, expect that to come up early.
Apply on company site
Opens job-boards.greenhouse.io, the employer's own application page. Applying is always free.