ValueLabs
Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Sr. Data Engineer/Analyst with 5+ years of experience, offering a remote contract position. Key skills include T-SQL, PySpark, Azure Databricks, and Snowflake. Familiarity with data warehousing principles and Agile frameworks is essential.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
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🗓️ - Date
October 23, 2025
🕒 - Duration
Unknown
-
🏝️ - Location
Remote
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
United States
-
🧠 - Skills detailed
#Azure Databricks #Vault #Data Profiling #Data Engineering #Data Lineage #PySpark #SQL (Structured Query Language) #Scripting #Data Design #Azure #Data Management #"ETL (Extract #Transform #Load)" #Scrum #SQL Server #Agile #BI (Business Intelligence) #Documentation #Data Architecture #Microsoft Power BI #ERWin #dbt (data build tool) #Python #Shell Scripting #Data Catalog #Data Governance #Data Vault #Metadata #Spark (Apache Spark) #Quality Assurance #Databricks #Snowflake #Data Analysis #Visualization #Cloud #Data Modeling
Role description
Role: Sr. Data Engineer / Analyst
Experience: 5+ years
Work location: Remote from US
Job Summary:
We are seeking a Data Engineer / Analyst to join our dynamic data architecture and analytics team. The ideal candidate will have strong hands-on experience with PySpark, T-SQL, and modern cloud-based data platforms such as Azure Databricks and Snowflake. This role requires end-to-end involvement in data analysis, transformation logic, functional data modeling, and lineage documentation. Understanding of data warehousing principles and Medallion Architecture is essential.
Responsibilities:
• Develop and maintain comprehensive data lineage documentation, SQL logic mapping, and technical design specifications to support seamless handoffs to Data Engineering and Data Governance teams.
• Collaborate with Data Architects and Analysts to ensure data models align with enterprise architecture and business objectives.
• Design, implement, and maintain efficient, reusable, and well-documented code in Python, T-SQL, and Shell Scripting.
• Partner with Business Intelligence SMEs and stakeholders to gather, define, and standardize functional and business-level data definitions.
• Perform detailed data profiling, validation, and quality assurance across structured and unstructured data sources.
• Participate in data discovery and functional analysis to inform data design decisions and support timely solution delivery.
Requirements:
• Minimum 5 years of experience in data engineering, analytics, or a related field.
• Proven expertise in T-SQL, PySpark, dbt, and Azure Databricks (including Spark Structured Streaming).
• Hands-on experience with SQL Server, Snowflake, Azure, or Microsoft Fabric.
• Familiarity with data modeling tools such as Erwin Data Modeler.
• Working knowledge of Power BI or equivalent BI/visualization tools.
• Solid understanding of data governance, metadata management, and data lineage principles.
• Experience working within Agile/Scrum delivery frameworks.
• Exposure to enterprise data warehousing methodologies such as Data Vault 2.0 or Kimball.
• Ability to translate complex business needs into clear, actionable technical solutions through structured analysis.
Preferred Qualifications (Nice to have):
• Experience supporting Medallion Architecture-based data platforms.
• Understanding of semantic layer design and data product delivery in modern BI environments.
• Exposure to data cataloging tools and metadata repositories (e.g., Azure Purview).
Role: Sr. Data Engineer / Analyst
Experience: 5+ years
Work location: Remote from US
Job Summary:
We are seeking a Data Engineer / Analyst to join our dynamic data architecture and analytics team. The ideal candidate will have strong hands-on experience with PySpark, T-SQL, and modern cloud-based data platforms such as Azure Databricks and Snowflake. This role requires end-to-end involvement in data analysis, transformation logic, functional data modeling, and lineage documentation. Understanding of data warehousing principles and Medallion Architecture is essential.
Responsibilities:
• Develop and maintain comprehensive data lineage documentation, SQL logic mapping, and technical design specifications to support seamless handoffs to Data Engineering and Data Governance teams.
• Collaborate with Data Architects and Analysts to ensure data models align with enterprise architecture and business objectives.
• Design, implement, and maintain efficient, reusable, and well-documented code in Python, T-SQL, and Shell Scripting.
• Partner with Business Intelligence SMEs and stakeholders to gather, define, and standardize functional and business-level data definitions.
• Perform detailed data profiling, validation, and quality assurance across structured and unstructured data sources.
• Participate in data discovery and functional analysis to inform data design decisions and support timely solution delivery.
Requirements:
• Minimum 5 years of experience in data engineering, analytics, or a related field.
• Proven expertise in T-SQL, PySpark, dbt, and Azure Databricks (including Spark Structured Streaming).
• Hands-on experience with SQL Server, Snowflake, Azure, or Microsoft Fabric.
• Familiarity with data modeling tools such as Erwin Data Modeler.
• Working knowledge of Power BI or equivalent BI/visualization tools.
• Solid understanding of data governance, metadata management, and data lineage principles.
• Experience working within Agile/Scrum delivery frameworks.
• Exposure to enterprise data warehousing methodologies such as Data Vault 2.0 or Kimball.
• Ability to translate complex business needs into clear, actionable technical solutions through structured analysis.
Preferred Qualifications (Nice to have):
• Experience supporting Medallion Architecture-based data platforms.
• Understanding of semantic layer design and data product delivery in modern BI environments.
• Exposure to data cataloging tools and metadata repositories (e.g., Azure Purview).
