Ampstek
Data Engineer (Contract W2)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer (Contract W2) in Texas, requiring 6+ years of experience with Databricks, Spark, Hive, AWS QuickSight, Python, and Django. The contract length and pay rate are unspecified.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
March 19, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
On-site
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
-
📍 - Location detailed
Texas, United States
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🧠 - Skills detailed
#Automated Testing #Azure #ADF (Azure Data Factory) #AWS EMR (Amazon Elastic MapReduce) #Spark (Apache Spark) #Scala #Big Data #Apache Spark #Datasets #Django #Spark SQL #Batch #"ETL (Extract #Transform #Load)" #PySpark #Documentation #Databricks #Data Processing #AWS (Amazon Web Services) #dbt (data build tool) #Data Engineering #Delta Lake #Python #SQL (Structured Query Language) #Azure Data Factory #Data Pipeline #Data Documentation
Role description
Role : Data Engineering
Location : Texas (Onsite)
Must Have Skills:
⦁ Databricks
⦁ Spark
⦁ Hive
⦁ AWS QuickSight
⦁ Python
⦁ Django
Minimum Years of Experience:
⦁ 6+ years
Nice to Have Skills:
Detailed Job Description:
Data Engineering & Big Data Development
⦁ Design and develop scalable, high‑performance data pipelines using:
1. Databricks (PySpark/SQL)
1. Apache Spark (batch & streaming)
1. Hive (query optimization, partitioning, bucketing)
1. AWS EMR (PySpark jobs for large-scale data processing)
1. Azure Data Factory (ADF) for ingestion and pipeline orchestration.
⦁ Build data processing frameworks to handle structured, semi‑structured, and unstructured datasets.
⦁ Develop highly optimized ETL/ELT workflows using Spark, SQL, Python.
⦁ Create curated data models (Bronze/Silver/Gold) using Databricks Delta Lake.
⦁ Optimize Spark transformations through:
1. Caching, checkpointing
1. Partition pruning
1. Adaptive query execution (AQE)
⦁ Build DBT models for:
1. SQL-based transformations
1. Automated testing
1. Lineage graphs
1. Data documentation to provide transparency across pipelines.
Thanks
Sandra
Sandra@ampstek.com
Role : Data Engineering
Location : Texas (Onsite)
Must Have Skills:
⦁ Databricks
⦁ Spark
⦁ Hive
⦁ AWS QuickSight
⦁ Python
⦁ Django
Minimum Years of Experience:
⦁ 6+ years
Nice to Have Skills:
Detailed Job Description:
Data Engineering & Big Data Development
⦁ Design and develop scalable, high‑performance data pipelines using:
1. Databricks (PySpark/SQL)
1. Apache Spark (batch & streaming)
1. Hive (query optimization, partitioning, bucketing)
1. AWS EMR (PySpark jobs for large-scale data processing)
1. Azure Data Factory (ADF) for ingestion and pipeline orchestration.
⦁ Build data processing frameworks to handle structured, semi‑structured, and unstructured datasets.
⦁ Develop highly optimized ETL/ELT workflows using Spark, SQL, Python.
⦁ Create curated data models (Bronze/Silver/Gold) using Databricks Delta Lake.
⦁ Optimize Spark transformations through:
1. Caching, checkpointing
1. Partition pruning
1. Adaptive query execution (AQE)
⦁ Build DBT models for:
1. SQL-based transformations
1. Automated testing
1. Lineage graphs
1. Data documentation to provide transparency across pipelines.
Thanks
Sandra
Sandra@ampstek.com
