US_East | Data Engineer_L3

Expedite Technology Solutions; King of Prussia (Montgomery County); Hybrid; USD 80,000 - 130,000; Full time

Job summary

An innovative firm is seeking a highly skilled Data Engineer to join their dynamic team. In this role, you will design and maintain scalable data platforms that support large-scale data ingestion, storage, and analysis. You will focus on constructing data products such as data lakes and warehouses, optimizing data pipelines, and implementing robust ETL workflows. The ideal candidate will have a strong background in cloud-based data architectures and distributed computing, with a passion for data-driven decision-making. If you thrive in a collaborative environment and are eager to work with cutting-edge technologies, this opportunity is perfect for you.

Qualifications

• 5+ years of experience in data engineering with large-scale data processing.
• Strong proficiency in SQL and Python for data transformation and analytics.
• Experience with cloud platforms like GCP and AWS.

Responsibilities

• Design and maintain scalable data platforms for efficient data processing.
• Build and optimize ETL pipelines using SQL and Python.
• Collaborate with data scientists and stakeholders in Agile teams.

Skills

SQL

Python

Data Engineering

Cloud Computing (GCP)

Real-time Data Streaming

MLOps

Data Modeling

Agile Development

Education

Bachelor's Degree in Computer Science

Master's Degree in Data Science

Tools

Kafka

Apache Beam

Terraform

Jenkins

CI/CD Tools

Job description

Possible 3 Month CTH | No Fees | Do Not Re-Post | Confidential
Skype interview is mandatory please provide the candidates skype ID, VIDEO INTERVIEW IS MANDATORY. NO CPT ALLOWED.

Submit candidates under their legal name and use only *** template
Candidate’s photo ID IS MANDATORY FOR ALL CANDIDATES EVEN CITIZENS.
------------------------------
In your submission include:
Phone #:
Email address:
Location (City and State):
Relocate:
Availability to start:
Visa type and expiration date:
Hiring Status: C2C/W2/1099QOpen for CTH (y/n):
Timeslots for Skype interview (provide Skype ID)
Due to additional onboarding requirements, a meet and greet is required for all new hires.
Candidates must be willing to go to the closest ***, Client, or offsite location as indicated by project team to meet with a *** team member prior to starting their assignment.
If the candidate is not local, travel will be required at the expense of the *** project team (will receive project code for vendor to submit invoices in SAP Fieldglass for reimbursement). If travel is involved, will send travel policy document for the candidate to adhere to

Vendors: If your candidate is selected for interview, you need to take screenshot of candidate and interviewer once interview is initiated. THIS IS NOW MANDATORY FOR ALL INTERVIEWS to confirm candidate is same as person in CV.

------------------------------
Marie Samayoa
OBO Tactical Procurement | Procurement
*** North America | Guatemala
Email: ***

Job Description: Data Engineer
Location: Philadelphia, PA
Client Specific Location
Open for remote work from East Coast

Our client is seeking a highly skilled Data Engineer to design, build, and maintain scalable data platforms that enable large-scale ingestion, storage, processing, and analysis of structured and unstructured data. This role will focus on constructing data products (data lake / data warehouse), optimizing data pipelines, and implementing robust ETL workflows to support analytics, machine learning, and operational reporting.
The ideal candidate will be proficient in distributed computing, cloud-based data architectures (GCP), and modern data processing frameworks. Experience with real-time data streaming (Kafka, Apache Beam), MLOps, and infrastructure automation (Terraform, Jenkins) is highly preferred.

Data Platform & Architecture Development
•Design, implement, and maintain scalable data platforms for efficient data storage, processing, and retrieval.
•Build cloud-native and distributed data systems that enable self-service analytics, real-time data processing, and AI-driven decision-making.
•Develop data models, schemas, and transformation pipelines that support evolving business needs while ensuring operational stability.
•Apply best practices in data modeling, indexing, and partitioning to optimize query performance, cost efficiency, considering best practices for Sustainability.
ETL, Data Pipelines & Streaming Processing
•Build and maintain highly efficient ETL pipelines using SQL, Python, to process large-scale datasets.
•Implement real-time data streaming pipelines using Kafka, Apache Beam, or equivalent technologies.
•Develop reusable internal data processing tools to streamline operations and empower teams across the organization.
•Write advanced SQL queries for extracting, transforming, and loading (ETL) data with a focus on execution efficiency.
•Ensure data validation, quality monitoring, and governance using automated processes and dashboards.
MLOps & Cloud-Based Data Infrastructure
•Deploy machine learning pipelines with MLOps best practices to support AI and predictive analytics applications.
•Optimize data pipelines for ML models, ensuring seamless integration between data engineering and machine learning workflows.
•Work with cloud platforms (GCP) to manage data storage, processing, and security.
•Utilize Terraform, Jenkins, CI/CD tools to automate data pipeline deployments and infrastructure management.
Collaboration & Agile Development
•Work in Agile/DevOps teams, collaborating closely with data scientists, software engineers, and business stakeholders.
•Advocate for data-driven decision-making, educating teams on best practices in data architecture and engineering.

•5+ years of experience as a Data Engineer working with large-scale data processing.
•Strong proficiency in SQL for data transformation, optimization, and analytics.
•Expertise in programming languages (Python, Java, Scala, or Go) with an understanding of functional and object-oriented programming paradigms.
•Experience with distributed computing frameworks.
•Proficiency in cloud-based data engineering on AWS, GCP, or Azure.
•Strong knowledge of data modeling, data governance, and schema design.
•Experience with CI/CD tools (Jenkins, Terraform) for infrastructure automation.

•Experience with real-time data streaming (Kafka, or equivalent).
•Strong understanding of MLOps and integrating data engineering with ML pipelines.
•Familiarity with knowledge graphs and GraphQL APIs for data relationships.
•Background in retail, customer classification, and personalization systems.
•Knowledge of business intelligence tools and visualization platforms.
•Retail industry experience, specifically Production of Consumer Goods