Data Engineer
Value Technology Inc
- Job
- 29506
- Posted
- Location
- Remote
- Work type
- Full Time
- Tax terms
- C2C
- Experience
- Experience open
- Rate
- $8 to $15 (Hourly)
- Openings
- 1 opening
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Skills
- SQL
- Python
- PySpark
- Spark
- Snowflake
- Databricks
- ETL
- Data Modeling
- Data Warehousing
- Azure
- CI/CD
- Scrum
About the job
Job Title: Data Engineer
Location: Remote
Experience: 8+ years
Job Summary
Value Technology is seeking an experienced Data Engineer with strong hands-on expertise in DBT, Snowflake, Azure Databricks, and Azure SQL. The ideal candidate will be responsible for designing, developing, and maintaining scalable data pipelines, transformation workflows, and cloud-based data solutions. The candidate should have strong SQL and Python skills and experience working with modern data engineering and cloud technologies.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines and ETL/ELT processes using modern cloud data engineering technologies.
- Develop and manage data transformation workflows using DBT, including models, tests, documentation, and incremental transformations.
- Build and optimize data solutions using Snowflake, including data loading, transformation, performance tuning, and warehouse optimization.
- Develop data engineering solutions using Azure Databricks, Apache Spark, PySpark, and SQL.
- Design, develop, and optimize databases, tables, views, stored procedures, and queries using Azure SQL.
- Develop robust batch and near-real-time data pipelines to support analytics, reporting, and business intelligence requirements.
- Implement data quality checks, validation rules, monitoring, and error-handling mechanisms.
- Optimize SQL queries, Spark jobs, DBT models, and Snowflake workloads for performance and cost efficiency.
- Integrate data from multiple sources including relational databases, APIs, cloud storage, and enterprise applications.
- Work with Azure services to implement secure and scalable cloud-based data solutions.
- Collaborate with Data Scientists, BI Developers, Analysts, Architects, and business stakeholders to understand data requirements.
- Implement data governance, security, lineage, and access-control practices.
- Participate in Agile/Scrum ceremonies, code reviews, technical discussions, and production support activities.
- Troubleshoot data pipeline failures and perform root-cause analysis for data quality and performance issues.
- Maintain technical documentation for data pipelines, DBT models, data architecture, and operational processes.
Required Skills
- Strong hands-on experience as a Data Engineer.
- Strong expertise in DBT and DBT-based data transformation.
- Strong experience with Snowflake data warehousing.
- Hands-on experience with Azure Databricks.
- Strong experience with Azure SQL.
- Advanced SQL development and query optimization skills.
- Strong Python programming skills.
- Experience with Apache Spark / PySpark.
- Strong understanding of ETL/ELT, data modeling, and data warehousing concepts.
- Experience developing scalable data pipelines and cloud-based data solutions.
- Experience with Git and CI/CD practices.
- Strong troubleshooting, analytical, and problem-solving skills.