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Temporary Data Engineer Jobs in New York (NOW HIRING)

Orion Innovation

Data Engineer

Montvale, NJ

$119K - $143K/yr

Hands-on Azure Data Engineering and Python experience. * Databricks + PySpark familiarity ... Advanced querying (CTEs, temp tables, correlated subqueries; cursors where appropriate)

Orion Innovation

Data Engineer

Montvale, NJ · On-site

$119K - $143K/yr

Hands-on Azure Data Engineering and Python experience. * Databricks + PySpark familiarity ... Advanced querying (CTEs, temp tables, correlated subqueries; cursors where appropriate)

Merican

Associate Data Engineer

Parsippany, NJ · On-site

$115K - $138K/yr

Temporary Assignment Work Type:Hybrid * We are seeking a hands-on Associate Data Engineer with strong programming skills in Python and SQL and practical experience building scalable data ingestion ...

T-Mobile

Senior Data Engineer, AdTech

New York, NY · On-site

$105K - $189K/yr

Job Responsibilities : * Develop data engineering solutions that enable data pipelines ... At T-Mobile, employees in regular, non-temporary roles are eligible for an annual bonus or periodic ...

Aquent

Sr. Data / M/L Engineer

Manhattan, NY · On-site

$76.50 - $85/hr

Temporary Salary: $76.50-85 Hourly Start Date: Jul 13, 2026 Hybrid on site in Union Square, NY. No ... Data modeling n -Infrastructure setup -Ability to work with large-scale datasets -Programming ...

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See New York salary details

$48.7K

$141.9K

$194.2K

How much do temporary data engineer jobs pay per year?

As of Aug 1, 2026, the average yearly pay for temporary data engineer in New York is $141,914.00, according to ZipRecruiter salary data. Most workers in this role earn between $125,300.00 and $150,400.00 per year, depending on experience, location, and employer.

What are the typical daily responsibilities of a Temporary Data Engineer?

As a Temporary Data Engineer, your day-to-day work often involves designing and maintaining data pipelines, cleaning and validating data, and implementing ETL processes to support business analytics or project objectives. You'll collaborate with data scientists, analysts, and other engineers to ensure data accuracy and system reliability, while troubleshooting issues or optimizing workflows as needs arise. Since this is a temporary role, you may also take on specialized short-term projects or support urgent business initiatives where fast, high-quality results are essential. The work environment is usually fast-paced, making adaptability and teamwork especially important for success.

What is a Temporary Data Engineer job?

A Temporary Data Engineer is a short-term role responsible for designing, building, and maintaining data pipelines and infrastructure. These professionals help organizations collect, store, and process data efficiently, often working on specific projects or to support peak workloads. Temporary Data Engineers typically use SQL, Python, and cloud platforms to manage data workflows. The role may last for weeks or months, depending on the company's needs.

What are the key skills and qualifications needed to thrive in the Temporary Data Engineer position, and why are they important?

To thrive as a Temporary Data Engineer, you need a solid grasp of data modeling, ETL processes, and SQL or other database languages, often supported by a degree in computer science or a related field. Familiarity with cloud platforms like AWS or Azure, experience with big data frameworks such as Apache Spark, and possibly certifications like Google Professional Data Engineer are valuable. Strong problem-solving skills, the ability to quickly adapt to new environments, and effective communication are important soft skills in this role. These abilities are crucial because Temporary Data Engineers must rapidly contribute to projects, ensure data systems run smoothly, and collaborate efficiently during short-term assignments.

What are the most commonly searched types of Data Engineer jobs in New York? The most popular types of Data Engineer jobs in New York are:
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Temporary Data Engineer jobs near you

Data Engineer

Orion Innovation

Montvale, NJ

$119K - $143K/yr

Other

Re-posted 26 days ago

Job description

Summary:
We seek an experienced Applications Lead (Technical Lead) to own technical support leadership for Data Analytics solution-supporting a global users across multiple Azure-based production environments. This is not an operations manager role; it is a hands-on technical leadership role focused on complex incident resolution, data-intensive troubleshooting, and performance / scalability in large datasets and pipelines.

You will serve as the escalation support technical lead for the most challenging cases (e.g., large datasets, heavy transformations, performance bottlenecks, configuration issues across data platforms), guiding support analysts and partnering with engineering/product to drive root cause closure and durable fixes. The role requires deep strength in PySpark, T-SQL, data engineering, and analytics platform troubleshooting across Databricks, SQL Server / DWH, Azure data services.

Qualifications:

  • 8+ years of experience in application support / technical lead / data platform troubleshooting roles, with demonstrated ownership of complex incident/problem resolution in production-like environments.
    Hands-on Azure Data Engineering and Python experience.
  • Databricks + PySpark familiarity, including:
    • Building/navigating workspaces and notebooks
    • PySpark read/write operations and basic transformation logic
  • Strong T SQL / DWH background, including:
    • SQL database design and development
    • Stored procedures, table & scalar functions, performance tuning via execution plans and indexing
    • Advanced querying (CTEs, temp tables, correlated subqueries; cursors where appropriate)
    • Experience with large-scale data wrangling, including scenarios with very large row counts (e.g., 100M+), and ability to reason about data complexity and performance bottlenecks.
    • Strong understanding of RDBMS concepts and (preferred) MSBI stack fundamentals.
    • Hands-on ETL and reporting experience, including troubleshooting of pipelines and data flows end-to-end.
    • Strong communication skills: ability to explain complex data/platform issues clearly to engineers, support teams, and stakeholders.

Preferred Experience

  • Hands-on SQL Diagnostics & Performance Tuning: Writing and optimizing advanced T SQL to diagnose and resolve issues (SPs, scalar/table functions, CTEs/temp tables, correlated subqueries; use execution plans, indexing strategy, and query refactoring for performance).
  • Azure Data Factory (ADF): building pipelines and troubleshooting orchestration patterns; ability to map concepts between SSIS and ADF.
  • ADLS file-format expertise: Parquet/Delta vs CSV/Excel tradeoffs for volume, performance, and operational supportability.
  • Power BI workspace concepts (nice to have), plus data management/data analysis tools like Alteryx (nice to have).
  • Basic accounting concepts to better interpret audit/financial datasets.
  • Advanced Excel (Pivot, formulas, lookups, VBA macros) as a nice to have.
  • SAP/Oracle ERP technical profile:
    • Understanding ERP architecture
    • Support implementation/customization/performance tuning of extraction code
    • Basic ABAP/UNIX familiarity as a nice to have

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