Data Engineering Lead

Jobgether; United States; Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Permanent remote

Flexible hours

Part-time opportunities

Welcome Back Program

Diversity & inclusion

Career growth

Job summary

Jobgether is seeking a Data Engineering Lead in the United States to design, build, and scale cloud-native data solutions. Lead architecture, mentor teams, and collaborate with stakeholders to deliver robust data products using AWS Glue, EMR, S3, Python, and PySpark.

The role emphasizes data integration, standards, quality, and performance in a remote-first, enterprise environment with opportunities for impact and growth.

Qualifications

• Experience with AWS data engineering in enterprise environments.
• Strong Python, PySpark, SQL and ETL/ELT development skills.
• Proven ability to design and optimize large-scale data pipelines.

Responsibilities

• Lead architecture, design, and development of scalable data pipelines using AWS Glue, EMR, S3, Python, and PySpark.
• Drive enterprise data integration and ETL/ELT workflows.
• Develop reliable, scalable data products and maintain engineering standards.

Skills

AWS data engineering

Python

PySpark

SQL

ETL/ELT

Data pipelines

Data integration

Technical leadership

Mentoring

Tools

AWS Glue

Amazon EMR

S3

Redshift

Athena

DynamoDB

Iceberg

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineering Lead based in the United States.

We are seeking an experienced Data Engineering Lead to drive the design, development, and delivery of scalable cloud-based data solutions. In this role, you will leverage AWS native services, Python, and PySpark to build robust data pipelines and modernize enterprise data platforms. You will play a key role in shaping data architecture, improving data integration, and developing high-performance data products. Working across complex enterprise environments, you will establish engineering standards and ensure the reliability, quality, and scalability of data solutions. You will also provide technical leadership, mentor engineering teams, and collaborate with architecture, technology, and business stakeholders. This is an opportunity to make a meaningful impact in a flexible, remote-first environment while contributing to large‑scale data transformation initiatives.

Responsibilities

• Lead the architecture, design, and development of scalable data pipelines using AWS Glue, EMR, S3, Python, and PySpark.


• Drive enterprise data integration initiatives and the implementation of ETL/ELT workflows.


• Lead the development of reliable, scalable, and reusable data products.


• Define and maintain engineering standards, best practices, and development guidelines.


• Conduct technical design reviews and code reviews to ensure solution quality and consistency.


• Optimize data pipelines for performance, data quality, processing efficiency, and scalability.


• Mentor and guide Data Engineers, supporting their technical development and delivery.


• Collaborate with architecture, technology, and business teams to align data engineering solutions with enterprise objectives.

Requirements

• Strong experience in AWS data engineering, particularly Amazon S3, AWS Glue, and Amazon EMR.


• Proficiency in Python, PySpark, SQL, and ETL/ELT development.


• Expertise in designing, developing, and optimizing large-scale data pipelines.


• Solid experience with enterprise data integration and complex data engineering environments.


• Proven ability to provide technical leadership, establish engineering standards, and conduct code and design reviews.


• Experience mentoring and guiding data engineering teams.

Preferred Qualifications

• Experience with Amazon Redshift, Athena, and DynamoDB.


• Knowledge of Apache Iceberg and modern data lake or lakehouse architectures.


• Familiarity with domain-oriented data products and authoritative data sources.


• Exposure to large-scale enterprise data platform modernization initiatives.

Benefits

• Permanent remote working model, with flexibility to work from anywhere within the eligible employment location.


• Flexible working arrangements adapted to individual, customer, and business needs.


• Potential for part-time schedules and working hours outside the traditional 9-to-5 framework.


• Welcome Back Program supporting individuals returning to work after an extended absence due to health or family circumstances.


• Inclusive and diverse working environment that values different perspectives and individual contributions.


• Opportunities to make a meaningful impact, develop your expertise, and grow professionally.

We appreciate your interest and wish you the best!

Data Privacy Notice:

By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre‑contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.