Data Engineer

Gigster Inc.; United States; Remote; USD 60,000 - 80,000; Part time

Job summary

Gigster Inc. is looking for a part-time Data Engineer to design and optimize data pipelines using technologies like Apache Spark and Kafka. The role includes integrating public APIs and collaborating with teams to enhance data processing for NLP models. This short-term contract offers flexible project choices and competitive pay rates.

Qualifications

• Experience in data processing and integration from public APIs.
• Hands-on experience with big data processing.
• Familiarity with financial services data is a plus.

Responsibilities

• Design, build, and optimize ETL/ELT data pipelines.
• Integrate external data sources and public APIs.
• Collaborate with teams to enhance NLP models.

Skills

Python

Data Transformation

ETL/ELT Processes

Collaboration

Tools

Apache Spark

Apache Kafka

Prefect

Airflow

Google Cloud Platform

PostgreSQL

Snowflake

Google BigQuery

Google Cloud Storage

Job description

Do you want to work on cutting-edge projects with the world’s best IT engineers? Do you wish you could control which projects to work on and choose your own pay rate? Are you interested in the future of work and how the cloud will form teams? If so - the Gigster Talent Network is for you.

Our clients rely on our Network for two main areas, Software Development and Cloud Services. In some cases, they need help building great new products, in others they want our expertise in migrating, maintaining, and optimizing their cloud solutions.

At Gigster, whether working with entrepreneurs to realize ‘the next great vision’ or with Fortune 500 companies to deliver a big product launch, we build really cool enterprise software on cutting-edge technology.

The Role:

We are seeking an experienced Data Engineer with deep expertise in data transformation at scale, particularly in integrating and processing data from third-party public APIs. This role is critical to enhancing and maintaining data pipelines that feed into Natural Language Processing (NLP) models.

What you’ll do:

Design, build, and optimize scalable ETL/ELT data pipelines usingApache Spark, Apache Kafka, and orchestration tools such as Prefect or Airflow

Integrate external data sources and public APIs with internal data systems

Work with large-scale datasets to support NLP model training and inference

Analyze existing pipelines and recommend enhancements for performance, reliability, and scalability

Collaborate with cross-functional teams, including data scientists and ML engineers

Own the end-to-end engineering process—from planning and technical design to implementation

Regularly report progress and outcomes to client stakeholders

What we’re looking for:

Proficiency in Python and experience with data transformation and data engineering best practices

Strong experience with Apache Spark, Apache Kafka, and Google Cloud Platform (GCP)

Hands-on experience with workflow orchestration tools (e.g., Prefect, Airflow)

Demonstrated experience working with large datasets and real-time data processing

Experience building and maintaining ETL/ELT pipelines for analytical or machine learning use cases

Self-motivated, with excellent communication and project ownership skills

Preferred Qualifications:

Familiarity with financial services data or regulated data environments

Experience with Snowflake or Google BigQuery

• Experience with PostgreSQL and GCS (Google Cloud Storage)

Exposure to NLP workflows and data requirements for machine learning models

Logistics:

• This is a part-time, short term, 4 to 6 weeks contract
• Preferred location: Remote US

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