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DataOps/Cloud Data Engineer

Softline Technology
Toronto, ON

Job details

Contract

Skills

Azure
Waterfall
Incident management
SQL
Pandas
AWS
Presentation skills
Scripting
S3
Linux
JSON
Informatica
Requirements gathering
Communication skills
Python
PowerShell
Negotiation
SDLC

Full job description

Description

Responsibilities:

Design, develop, test, implement, and troubleshoot:

data pipelines using various tools such as Databricks, Azure Data Factory, AWS Glue

complex data transformation procedures

data models for data warehouses and lakehouses

Experience Requirements

Data engineering Experience

Programming &
scripting: Python, SQL, Linux
shell, PowerShell.
Data
manipulation/analysis using pandas and pyspark.
Working with
XLSX, CSV, JSON files, relational databases, cloud storage, structured
and unstructured data

40%

Cloud experience

AWS and/or Azure services.
Cloud data
warehouse solutions such as AWS Redshift.
Data lakehouse solutions such as Databricks (Delta
Lake).
Data processing
orchestration/automation

25%

Data Warehouse

ETL tools (such as Azure
Data Factory, AWS Glue) as well as cloud agnostic tools such as
Informatica IDMC.
Data modeling & architecture: relational and dimensional
modeling.
Data reporting/visualization.

25%

Other
Skills

Full SDLC
from requirements gathering, design, implementation, testing to
deployment and production support
Project
management (agile/scrum and waterfall)
Change and
Incident management
Communication,
presentation and negotiation skills
Consulting, problem-solving
and decision-making skills

Public Sector

Experience
working in OPS and/or public sector in general

Supplier Comments

**Repost**

Closing Date/Time: 2026-06-17, 12:00 p.m.

Max submission: 1 (one)

5 days onsite

Assignment Type: This position is listed as Onsite; the resource is expected to work 7.25 hours per calendar day between the standard working hours of 8:00-5:00 PM (excluding lunch breaks) every Monday to Friday inclusive at the identified OPS office location.

MUST HAVES:

Data engineering (pandas, pyspark)

Data lakehouse solutions such as Databricks (Delta Lake).

Working with XLSX, CSV, JSON files, relational databases, cloud storage, structured and unstructured data

Experience using AWS Services such as Glue, StepFunctions, Lambda, S3

Extract/Transform/Load data using tools such as Informatica IDMC

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