

Data Engineer (Python)
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer (Python) in Houston, TX, on a 6+ month contract, offering competitive pay. Requires 12+ years in software development, 5+ years in Python, and expertise in Data Lakehouse solutions, SQL, and data modeling techniques.
π - Country
United States
π± - Currency
$ USD
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π° - Day rate
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ποΈ - Date discovered
July 10, 2025
π - Project duration
More than 6 months
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ποΈ - Location type
On-site
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π - Contract type
W2 Contractor
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π - Security clearance
Unknown
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π - Location detailed
Houston, TX
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π§ - Skills detailed
#Kubernetes #Vault #Airflow #Data Engineering #Datasets #"ETL (Extract #Transform #Load)" #Data Access #Data Quality #Data Vault #Scala #Visualization #Delta Lake #Data Lakehouse #Data Lake #NumPy #Snowflake #Security #Big Data #Cloud #Physical Data Model #Python #Libraries #GIT #Data Pipeline #AWS (Amazon Web Services) #SQL (Structured Query Language) #Apache Airflow #Pandas #Apache Iceberg #Dremio #S3 (Amazon Simple Storage Service) #Storage #Data Modeling #dbt (data build tool) #Data Storage #Version Control #Pytest #Data Integration
Role description
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Dice is the leading career destination for tech experts at every stage of their careers. Our client, Providence Partners, is seeking the following. Apply via Dice today!
Data Engineer (Python)
Location: Houston, TX (Onsite)
Duration: 6+ Months Contract
Position Overview
We are seeking a highly skilled Senior Python Data Engineer to join our Big Data and Advanced Analytics team. This role will be critical in designing and building a modern Enterprise Data Lakehouse to support advanced analytics initiatives for the midstream oil and gas sectors, including operations, engineering, and measurement units.
This is an exciting opportunity to work on cutting-edge data engineering projects that drive real business impact. If you're passionate about building modern data platforms and solving complex data problems in a fast-paced environment, we d love to hear from you.
The ideal candidate is a seasoned data engineer with extensive hands-on experience in Python, Data Lakehouse architectures, and cloud-native data engineering tools.
Key Responsibilities
β’ Design, develop, and maintain scalable and reliable data pipelines to ingest and transform structured and unstructured data from various sources.
β’ Implement data quality pipelines to validate, cleanse, and ensure the trustworthiness of business-critical datasets.
β’ Architect and build a robust Data Lakehouse solution using Apache Iceberg or similar frameworks, aligned with business logic and operational requirements.
β’ Optimize performance of the data platform including physical data modeling, partitioning, and compaction strategies.
β’ Collaborate with business stakeholders to translate requirements into effective data engineering solutions.
β’ Provide guidance on data visualization and reporting strategies to ensure alignment with business goals.
β’ Participate in performance tuning, CI/CD implementation, and adhere to software engineering best practices.
Required Qualifications
β’ 12+ years of experience in software development or software engineering.
β’ 5+ years of hands-on experience with Python, including use of libraries like Pandas, NumPy, PyArrow, Pytest, Boto3, and Scikit-Learn.
β’ Strong experience in SQL and modern data modeling techniques including Star Schema, Snowflake Schema, and Data Vault.
β’ 2+ years of hands-on experience using DBT (Data Build Tool) for data transformation.
β’ Proven experience implementing Data Lakehouse solutions using Apache Iceberg or Delta Lake on S3 object storage.
β’ Knowledge of data integration patterns including ELT, Change Data Capture (CDC), and Pub/Sub messaging.
β’ Strong understanding of software development principles, including design patterns, testing, refactoring, CI/CD pipelines, and version control (e.g., Git).
β’ Excellent communication skills, capable of conveying complex technical concepts to both technical and non-technical audiences.
Preferred Skills (Nice To Have)
β’ Experience with Python-based UI frameworks, particularly Dash.
β’ Exposure to Dremio, Apache Airflow, or Airbyte for orchestration and data access.
β’ Familiarity with Kubernetes and AWS EKS.
β’ Hands-on experience working with AWS Cloud services related to data storage, processing, and security.