Skip to main content
Loading
loadingbar
Loading, Please wait..!!

Data Warehouse Engineer

  • Data Warehouse Engineer job type Posted on: Oct 28, 2026
  • Data Warehouse Engineer experience level Saransh Inc
  • Data Warehouse Engineer employment type New York, New York
  • Data Warehouse Engineer employment type Onsite
  • Data Warehouse Engineer salary CTC

Point Apply Here APPLY LATER

Curious about compensation?

Explore the historical salary trends, average pay, and estimated compensation for Data Warehouse Engineer roles in New York.

View Salary Guide →

Job Title :

Data Warehouse Engineer

Job Type :

Contract

Job Location :

New York New York United States

Remote :

No

Jobcon Logo Job Description :

Position Title: Data Warehouse Engineer
Location: New York, NY (5 Days Onsite)
Duration: 6 Months Contract
Job Description:
The client is strategically transitioning the Data Warehouse engineering operations onshore and is looking for a driven Data Warehouse Engineer to help lead this initiative.
Your primary focus will be migrating, building, and optimizing ELT pipelines that extract data from third-party APIs and load it into our data lake utilizing managed Delta tables.
You will initially work closely with our existing offshore team to complete a comprehensive Knowledge Transfer (KT).
Key Responsibilities:
ELT Pipeline Development: Design, build, and maintain robust ELT (Extract, Load, Transform) pipelines to migrate data from various third-party API sources into our enterprise data lake.
Databricks Ecosystem: Create, manage, and optimize managed Delta tables within a Databricks environment to ensure high data reliability and query performance.
API Integration: Securely connect to, authenticate with, and extract data from a wide variety of third-party RESTful APIs.
Data Modeling & Querying: Write clean, scalable, and efficient Python and SQL code to transform raw data into analytics-ready datasets.
Knowledge Transfer (KT): Actively participate in onboarding and KT sessions with the current offshore team to seamlessly transition ownership of existing pipelines and architecture.
Documentation: Maintain clear technical documentation for data pipelines, API integrations, and Delta table schemas to support future onshore hires.
Required Skills & Qualifications:
Experience: 6+ years of experience in data engineering, data warehousing.
Core Languages: Strong, hands-on proficiency in Python and SQL.
Databricks & Data Lakes: Practical experience working with Databricks, specifically building and maintaining Delta tables and working within a modern data lake architecture.
API Expertise: Proven experience extracting and handling data from third-party APIs (handling pagination, rate limiting, JSON/XML parsing, etc.).
Methodology: Solid understanding of ELT methodologies and cloud-based data architecture.
Communication: Excellent verbal and written communication skills, with the ability to effectively absorb complex technical information during cross-border knowledge transfers.

Jobcon Logo Position Details

Posted:

Oct 28, 2026

Reference Number:

5031-2279

Employment:

CTC

City:

New York

Job Origin:

CIEPAL_ORGANIC_FEED

Share this job:

  • linkedin

Jobcon Logo
A job sourcing event
In Dallas Fort Worth
Aug 19, 2017 9am-6pm
All job seekers welcome!

Data Warehouse Engineer    Apply

Click on the below icons to share this job to Linkedin, Twitter!

Position Title: Data Warehouse Engineer
Location: New York, NY (5 Days Onsite)
Duration: 6 Months Contract
Job Description:
The client is strategically transitioning the Data Warehouse engineering operations onshore and is looking for a driven Data Warehouse Engineer to help lead this initiative.
Your primary focus will be migrating, building, and optimizing ELT pipelines that extract data from third-party APIs and load it into our data lake utilizing managed Delta tables.
You will initially work closely with our existing offshore team to complete a comprehensive Knowledge Transfer (KT).
Key Responsibilities:
ELT Pipeline Development: Design, build, and maintain robust ELT (Extract, Load, Transform) pipelines to migrate data from various third-party API sources into our enterprise data lake.
Databricks Ecosystem: Create, manage, and optimize managed Delta tables within a Databricks environment to ensure high data reliability and query performance.
API Integration: Securely connect to, authenticate with, and extract data from a wide variety of third-party RESTful APIs.
Data Modeling & Querying: Write clean, scalable, and efficient Python and SQL code to transform raw data into analytics-ready datasets.
Knowledge Transfer (KT): Actively participate in onboarding and KT sessions with the current offshore team to seamlessly transition ownership of existing pipelines and architecture.
Documentation: Maintain clear technical documentation for data pipelines, API integrations, and Delta table schemas to support future onshore hires.
Required Skills & Qualifications:
Experience: 6+ years of experience in data engineering, data warehousing.
Core Languages: Strong, hands-on proficiency in Python and SQL.
Databricks & Data Lakes: Practical experience working with Databricks, specifically building and maintaining Delta tables and working within a modern data lake architecture.
API Expertise: Proven experience extracting and handling data from third-party APIs (handling pagination, rate limiting, JSON/XML parsing, etc.).
Methodology: Solid understanding of ELT methodologies and cloud-based data architecture.
Communication: Excellent verbal and written communication skills, with the ability to effectively absorb complex technical information during cross-border knowledge transfers.

Loading
Please wait..!!