Senior Big Data Software Engineer (Snowflake + DBT)
SoftServe, Inc.
United States
7 days ago
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Role details
Contract type
Permanent contract
Employment type
Part-time (β€ 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Languages
English
Job source
Tech stack
Airflow
Amazon Web Services
Big Data
Cloud Engineering
Continuous Integration
Information Engineering
Extract Transform Load (ETL)
Data Transformation
Data Systems
Data Warehousing
Digital Assets
Python (Programming Language)
+8 more
Cloud Services
SQL Databases
Workflow Management Systems
Data Processing
Sql Optimization
Snowflake
Software Version Control
Data Pipelines
Job description
In this role you will design and develop scalable data warehouse and ELT solutions that support analytics and business decision-making. You will take ownership of reliable data workflows and large-scale analytical datasets, working with technical and business stakeholders to deliver high-quality data assets with a focus on performance, data quality, and cost efficiency., * Design, develop, and maintain scalable ETL/ELT pipelines and data warehouse solutions to support reliable analytics and business decision-making
- Build and optimize data transformations and data models, using Snowflake, dbt, SQL, and Python.
- Collaborate with technical and business stakeholders to understand requirements and translate them into effective data solutions and high-quality data assets
- Develop and maintain workflow orchestration using Apache Airflow to support reliable end-to-end data processing
- Design data models and ingestion frameworks that support large-scale analytical datasets and complex data transformations
- Implement data quality, validation, and auditing processes across end-to-end data workflows to improve the reliability of data assets
- Develop and maintain data integration solutions across AWS and Snowflake environments using SQL, Python, and dbt
- Contribute to CI/CD, testing, troubleshooting, and continuous improvement practices for data engineering solutions in production environments
Requirements
- Strong experience in Data Engineering, Data Warehousing, or related fields, with 5+ years of professional experience
- Strong hands-on experience with Snowflake and modern cloud-based data warehouse solutions
- Advanced SQL skills for working with large-scale datasets and complex data transformations
- Strong proficiency in Python for data engineering, data transformation, and automation
- Hands-on experience with dbt for data transformation, modeling, testing, and documentation
- Solid experience designing and maintaining ETL/ELT pipelines, data models, and ingestion workflows
- Practical experience with Apache Airflow or similar workflow orchestration technologies
- Hands-on experience with AWS cloud data platforms and services, plus familiarity with CI/CD, version control, data quality, and production troubleshooting practices
- Upper-intermediate or higher English proficiency for collaboration with technical and business stakeholders
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