PineQ Lab Technology
Tech Lead- Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Tech Lead- Data Engineer with 15+ years of experience, focusing on Python, PySpark, AWS, SQL, and data pipeline development. Contract length is unspecified, with a competitive pay rate. Remote work is available.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
June 4, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Malvern, PA
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🧠 - Skills detailed
#Python #PySpark #AWS (Amazon Web Services) #DynamoDB #Redshift #Spark (Apache Spark) #Data Processing #Compliance #Athena #Lambda (AWS Lambda) #Data Modeling #S3 (Amazon Simple Storage Service) #Cloud #SQL (Structured Query Language) #AWS S3 (Amazon Simple Storage Service) #Data Pipeline #Data Engineering #Terraform #Security #GIT #Data Security #"ETL (Extract #Transform #Load)" #Airflow
Role description
15+ years of professional experience in Data Engineering.
Strong expertise in Python and PySpark for large-scale data processing.
Advanced hands-on experience with AWS (S3, Glue, EMR, Lambda, Step Functions, Kinesis/MSK, DynamoDB, Athena, Redshift).
Deep experience building event-driven and streaming data pipelines.
Strong SQL experience for analytical and ETL workloads.
Hands-on experience with workflow orchestration tools such as Airflow or Step Functions.
Experience with CI/CD, Git, and Infrastructure-as-Code (Terraform or CloudFormation).
Strong understanding of distributed systems, Spark performance tuning, data modeling, and cloud cost optimization.
Knowledge of data security, encryption, networking, and compliance best practices in cloud environments.
15+ years of professional experience in Data Engineering.
Strong expertise in Python and PySpark for large-scale data processing.
Advanced hands-on experience with AWS (S3, Glue, EMR, Lambda, Step Functions, Kinesis/MSK, DynamoDB, Athena, Redshift).
Deep experience building event-driven and streaming data pipelines.
Strong SQL experience for analytical and ETL workloads.
Hands-on experience with workflow orchestration tools such as Airflow or Step Functions.
Experience with CI/CD, Git, and Infrastructure-as-Code (Terraform or CloudFormation).
Strong understanding of distributed systems, Spark performance tuning, data modeling, and cloud cost optimization.
Knowledge of data security, encryption, networking, and compliance best practices in cloud environments.
