Data Delivery Lead

Jobtailor; Toronto; On-site; CAD 90,000 - 130,000; Full time

Job summary

Jobtailor is seeking a data analytics/engineering professional in Toronto to own end-to-end data deliveries. You will pull data from internal systems, format to customer schemas, and hand off to cloud storage with strong QA and validation.

You will work across SQL, Python, and modern data warehouses, ensuring timely delivery against SLAs in a fast-growing startup. This role emphasizes data quality, governance, and scalable data workflows.

Qualifications

• 1–3 years in data analytics, data engineering, analytics engineering, or similar data-heavy role.
• Fluent in SQL; able to query and reshape large datasets independently.
• Working proficiency with Python for data manipulation, validation, and automation.
• Strong grasp of data pipelines, schemas, and data-quality concepts.
• Proven ability to own a data workflow or deliverable end-to-end.
• Excellent communication and stakeholder-management abilities.
• Experience in fast-paced startups or high-growth environments.
• Exposure to ML/AI training data, data labeling, or dataset delivery.
• Experience with NoSQL / document stores and/or columnar analytics databases.
• Experience with ClickHouse, BigQuery, or Snowflake.
• Built QA / validation tooling or data-quality checks.
• Strong prioritization and tradeoff instincts between speed, quality, and cost.
• Rigorous and detail-obsessed.

Responsibilities

• Pull final delivery cuts from internal systems and format data to customer schemas.
• Generate manifests, indexes, and packaging for delivery.
• Stage and hand off deliveries to customer buckets and cloud storage.
• Own delivery mechanics end-to-end and run through ship-gates.
• Design validation including coverage stats, audits, and schema checks.
• Build and maintain golden reference sets and repeatable quality checks.
• Translate customer data specs into gates and queries.
• Produce delivery reports, data catalogs, and schema documentation.
• Track delivery performance against timelines and SLAs.
• Identify and remove bottlenecks in the delivery process.
• Scale the delivery process as volume grows.

Skills

SQL Proficiency

Data Pipelines

Data Quality

Python Scripting

End-to-end Ownership

Tools

SQL

Python

NoSQL Databases

Document Stores

ClickHouse

BigQuery

Snowflake

Job description

• Pull final delivery cuts from internal data systems, including document and columnar databases and file stores
• Format data to customer schemas and generate manifests, indexes, and packaging
• Stage and reliably and reproducibly hand off deliveries to customer buckets and cloud storage
• Own delivery mechanics end-to-end
• Run every deliverable through internal ship-gates
• Design and execute validation including coverage statistics, stratified sample audits, schema compliance, and quality-drift detection
• Set an internal acceptance bar higher than the customer's QC
• Build and maintain golden reference sets and repeatable quality checks
• Translate customer data specifications into concrete, testable gates and queries
• Translate customer requirements into capture, labeling, and computer-vision operations requirements
• Serve as technical interpreter between customer requirements and internal execution
• Produce delivery reports, data catalogs, sample packs, and schema documentation
• Maintain a current canonical reference pack
• Track delivery performance against timelines and SLAs
• Identify and remove bottlenecks in the assembly-to-ship process
• Scale the delivery process as volume and customer count grow
• Partner with data capture, labeling operations, and engineering to close specification gaps
• Own delivery communication with internal teams and external customers
• Keep timelines, risks, and deliverable status transparent

Requirements

• 1–3 years in data analytics, data engineering, analytics engineering, or a similarly data-heavy role
• Fluent in SQL; comfortable querying and reshaping large, imperfect datasets independently
• Working proficiency with a scripting language (Python preferred) for data manipulation, validation, and automation
• Solid grasp of data pipelines, schemas, and data-quality concepts
• Proven ability to own a data workflow or deliverable end-to-end
• Excellent communication and stakeholder-management abilities
• Experience in fast-paced startups or high-growth environments
• Exposure to ML / AI training data, data labeling, or dataset delivery
• Experience with NoSQL / document stores and/or columnar analytics databases
• Experience with ClickHouse, BigQuery, or Snowflake
• Built QA / validation tooling or data-quality checks
• Strong intuition for prioritization and tradeoffs between speed, quality, and cost
• Rigorous and detail-obsessed
• Structured in thinking but flexible in execution
• Comfortable operating in ambiguity and fast-changing environments
• Data-native; instinct to measure, not assume
• Calm under pressure and able to run multiple deliveries in parallel without dropping quality

Core Competencies

Demonstrates expertise in data analytics and engineering, with a strong focus on SQL, data quality, and validation processes. Capable of managing end-to-end data workflows while ensuring high standards of communication and stakeholder management.

Highest-signal resume keywords

• SQL Proficiency
• Data Pipeline Management
• Data Quality Assurance
• Python Scripting for Data Manipulation
• Experience with ClickHouse, BigQuery, or Snowflake

ATS Optimization Keywords

Hard Skills

• Data Analytics
• Data Engineering
• Data Quality Concepts
• Data Manipulation
• Data Validation
• Data Schemas
• Data Workflows
• Data Delivery
• Data Cataloging
• Data Performance Tracking

Soft Skills

• Excellent Communication
• Stakeholder Management
• Detail-Oriented
• Structured Thinking
• Calm Under Pressure

Industry Keywords

• Data Capture
• Data Labeling
• ML / AI Training Data
• High-Growth Environments
• Fast-Paced Startups

Tools & Technologies

• SQL
• Python
• NoSQL Databases
• Document Stores
• Columnar Analytics Databases
• ClickHouse
• BigQuery
• Snowflake