Loading, Please wait..!!
Data Warehouse Engineer
-
Posted on: Oct 28, 2026
-
New York, New York
-
Onsite
-
CTC
Curious about compensation?
Explore the historical salary trends, average pay, and estimated compensation for Data Warehouse Engineer roles in New York.
View Salary Guide →
Over 12 millions jobs on Snaprecruit.
Find your match !
VIEW SIMILAR JOBS →
Find your match !
Job Title :
Data Warehouse Engineer
Job Type :
Contract
Job Location :
New York New York United States
Remote :
No
Job Description :
Position Title: Data Warehouse Engineer
Location: New York, NY (5 Days Onsite)
Duration: 6 Months Contract
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).
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.
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.
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.
Similar Jobs You May Be Interested In
Intern - Associate Solutions Engineer - Data Warehouse
Confidential Employer
Effingham, Illinois
Intern - Associate Solutions Engineer - Data Warehouse
Confidential Employer
Saint Louis, Missouri
Data Warehouse Engineer
Confidential Employer
Denver, Colorado
Lead Clinical Data Warehouse Engineer
Confidential Employer
New York, New York
Data Governance Engineer With Data Warehouse
Confidential Employer
New York City, New York
Data Warehouse Engineer
Confidential Employer
Kenosha, Wisconsin
Data Warehouse Engineer
Confidential Employer
Denver Metropolitan Area, Colorado
Databricks Data Warehouse Engineer
Confidential Employer
United States, Pennsylvania
Position Details
Posted:
Oct 28, 2026
Reference Number:
5031-2279
Employment:
CTC
City:
New York
Job Origin:
CIEPAL_ORGANIC_FEED
Share this job:
Please wait..!!

