SoftStandard Solutions
Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer with a contract length of "unknown," offering a pay rate of "unknown." Key skills include Python, SQL, Apache Spark, Kafka, and cloud platforms (AWS, Azure, GCP). Experience with data warehousing and ETL processes is required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
July 24, 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
United States
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🧠 - Skills detailed
#Data Science #Databases #Databricks #Azure #Apache Spark #Scrum #Batch #Scala #Snowflake #Data Warehouse #Data Architecture #Amazon Redshift #Python #Data Quality #Kubernetes #Database Performance #BigQuery #Data Analysis #AWS (Amazon Web Services) #Docker #SQL (Structured Query Language) #Spark (Apache Spark) #Data Pipeline #Data Integration #Airflow #Data Engineering #"ETL (Extract #Transform #Load)" #Kafka (Apache Kafka) #GCP (Google Cloud Platform) #Apache Airflow #Agile #BI (Business Intelligence) #GIT #Data Modeling #Data Lake #SQL Queries #Documentation #Redshift #Code Reviews #Cloud #NoSQL #Security
Role description
Data Engineer Job Description
Job Title: Data Engineer
Job Summary:
Roles & Responsibilities
• Design, develop, and maintain scalable data pipelines for processing large volumes of structured and unstructured data.
• Build and optimize ETL/ELT workflows using modern data integration tools and frameworks.
• Develop and manage data warehouses, data lakes, and cloud-based data platforms.
• Integrate data from multiple sources, including databases, APIs, streaming platforms, and third-party systems.
• Ensure data quality, integrity, governance, and security across all data assets.
• Write, optimize, and maintain complex SQL queries and stored procedures.
• Develop data transformation and processing solutions using Python, Spark, or similar technologies.
• Collaborate with Data Scientists, Data Analysts, BI Developers, and Software Engineers to deliver scalable data solutions.
• Monitor, troubleshoot, and optimize data pipelines to ensure high availability and performance.
• Implement data modeling techniques and optimize database performance.
• Work with cloud platforms such as AWS, Azure, or GCP to build and maintain data infrastructure.
• Develop and maintain real-time and batch processing solutions using technologies such as Kafka and Spark.
• Automate workflows using orchestration tools such as Apache Airflow.
• Participate in code reviews and implement software engineering best practices.
• Maintain technical documentation for data architecture, pipelines, and processes.
• Work in an Agile/Scrum environment and collaborate with cross-functional teams to deliver business requirements.
Required Skills
• Strong experience with Python and SQL.
• Hands-on experience with Apache Spark, Kafka, and Apache Airflow.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
• Knowledge of Snowflake, Databricks, Amazon Redshift, or Google BigQuery.
• Experience with relational and NoSQL databases.
• Strong understanding of data warehousing concepts and dimensional modeling.
• Familiarity with Docker, Kubernetes, Git, and CI/CD pipelines.
• Excellent analytical, problem-solving, and communication skills.
.
Data Engineer Job Description
Job Title: Data Engineer
Job Summary:
Roles & Responsibilities
• Design, develop, and maintain scalable data pipelines for processing large volumes of structured and unstructured data.
• Build and optimize ETL/ELT workflows using modern data integration tools and frameworks.
• Develop and manage data warehouses, data lakes, and cloud-based data platforms.
• Integrate data from multiple sources, including databases, APIs, streaming platforms, and third-party systems.
• Ensure data quality, integrity, governance, and security across all data assets.
• Write, optimize, and maintain complex SQL queries and stored procedures.
• Develop data transformation and processing solutions using Python, Spark, or similar technologies.
• Collaborate with Data Scientists, Data Analysts, BI Developers, and Software Engineers to deliver scalable data solutions.
• Monitor, troubleshoot, and optimize data pipelines to ensure high availability and performance.
• Implement data modeling techniques and optimize database performance.
• Work with cloud platforms such as AWS, Azure, or GCP to build and maintain data infrastructure.
• Develop and maintain real-time and batch processing solutions using technologies such as Kafka and Spark.
• Automate workflows using orchestration tools such as Apache Airflow.
• Participate in code reviews and implement software engineering best practices.
• Maintain technical documentation for data architecture, pipelines, and processes.
• Work in an Agile/Scrum environment and collaborate with cross-functional teams to deliver business requirements.
Required Skills
• Strong experience with Python and SQL.
• Hands-on experience with Apache Spark, Kafka, and Apache Airflow.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
• Knowledge of Snowflake, Databricks, Amazon Redshift, or Google BigQuery.
• Experience with relational and NoSQL databases.
• Strong understanding of data warehousing concepts and dimensional modeling.
• Familiarity with Docker, Kubernetes, Git, and CI/CD pipelines.
• Excellent analytical, problem-solving, and communication skills.
.
