Canonical Data Engineer
Budget: ₹600 – ₹5,000 INR
Federal Data Operations Specialist
(Canonical Company Lists, Upstream of CRM)
Engagement Type
Contract / Part-time
Remote
Ongoing or project-based, depending on workload
Engagement: Fixed-price, per-deliverable (project-based)
Role ObjectiveGraviton builds outbound and CRM systems on top of canonical company datasets.This role exists to create those datasets upstream of CRM, by correctly merging multiple raw data sources into clean, deterministic, company-level tables using stable identifiers.Accuracy, correctness, and discipline matter more than speed.
Core Responsibilities
You will:
Merge multiple datasets with different levels of granularity into a single canonical table
Enforce a primary identifier (e.g., UEI, CAGE, or equivalent) as the identity anchor
Aggregate transaction-level data to the entity (company) level correctly
Apply explicit join logic (inner, left, etc.) based on written rules
Produce one-row-per-entity outputs suitable for reuse downstream
Deliver clean, well-structured CSV outputs with no duplication
All work happens before CRM, sales, or marketing systems.
Required Core Competency (Non-Negotiable)
You must be very comfortable with SQL and relational data concepts, including:
GROUP BY and aggregation logic
Join types and their implications
Primary keys vs display fields
Entity-level vs transaction-level data
Deterministic merges (rules-based, not heuristic)
You may execute work in SQL, Excel, or Google Sheets — but you must think in SQL terms.
Working Style Expectations
You follow SOPs exactly
You do not invent logic or “clean things up” subjectively
When rules are unclear or data conflicts exist, you stop and flag
You prefer correctness over speed
You surface data integrity risks early
What This Role Is NOT
This role does not include:
CRM cleanup or deduplication inside HubSpot
Contact enrichment (emails or phone numbers)
Lead scoring or prioritization
Marketing segmentation
Outreach preparation
Those functions occur after your work is complete.
Required Skills & Experience
Strong SQL knowledge (required)
Experience merging and normalizing real-world datasets
High attention to detail
Comfortable working from written SOPs
Clear communicator when flagging ambiguity or data issues
Federal domain experience is not required.
How to Apply
Applicants should include:
Brief description of prior data merge / normalization work
Tools used (SQL dialects, Excel, Sheets, etc.)
Confirmation that they are comfortable stopping and flagging issues rather than guessing
(Canonical Company Lists, Upstream of CRM)
Engagement Type
Contract / Part-time
Remote
Ongoing or project-based, depending on workload
Engagement: Fixed-price, per-deliverable (project-based)
Role ObjectiveGraviton builds outbound and CRM systems on top of canonical company datasets.This role exists to create those datasets upstream of CRM, by correctly merging multiple raw data sources into clean, deterministic, company-level tables using stable identifiers.Accuracy, correctness, and discipline matter more than speed.
Core Responsibilities
You will:
Merge multiple datasets with different levels of granularity into a single canonical table
Enforce a primary identifier (e.g., UEI, CAGE, or equivalent) as the identity anchor
Aggregate transaction-level data to the entity (company) level correctly
Apply explicit join logic (inner, left, etc.) based on written rules
Produce one-row-per-entity outputs suitable for reuse downstream
Deliver clean, well-structured CSV outputs with no duplication
All work happens before CRM, sales, or marketing systems.
Required Core Competency (Non-Negotiable)
You must be very comfortable with SQL and relational data concepts, including:
GROUP BY and aggregation logic
Join types and their implications
Primary keys vs display fields
Entity-level vs transaction-level data
Deterministic merges (rules-based, not heuristic)
You may execute work in SQL, Excel, or Google Sheets — but you must think in SQL terms.
Working Style Expectations
You follow SOPs exactly
You do not invent logic or “clean things up” subjectively
When rules are unclear or data conflicts exist, you stop and flag
You prefer correctness over speed
You surface data integrity risks early
What This Role Is NOT
This role does not include:
CRM cleanup or deduplication inside HubSpot
Contact enrichment (emails or phone numbers)
Lead scoring or prioritization
Marketing segmentation
Outreach preparation
Those functions occur after your work is complete.
Required Skills & Experience
Strong SQL knowledge (required)
Experience merging and normalizing real-world datasets
High attention to detail
Comfortable working from written SOPs
Clear communicator when flagging ambiguity or data issues
Federal domain experience is not required.
How to Apply
Applicants should include:
Brief description of prior data merge / normalization work
Tools used (SQL dialects, Excel, Sheets, etc.)
Confirmation that they are comfortable stopping and flagging issues rather than guessing