What are the responsibilities and job description for the Data Engineer position at Raas Infotek LLC?
Job Details
Job Title: Data Engineer
Duration: 12 Months
Location: Franklin, TN (Hybrid)
Contract: W2 Only
Job Summary
We are looking for a highly experienced Data Engineer with 12 years of expertise in cloud data warehousing, data modeling, and data pipeline development. The ideal candidate will have strong proficiency in Google Cloud Platform (Google Cloud Platform), Snowflake, SQL, and Python while also demonstrating a passion for data quality, scalability, and performance optimization. This role will involve working on big data processing, cloud-based data solutions, and machine learning-driven insights.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines and ETL processes using Google Cloud Storage, Cloud SQL, and BigQuery.
- Build and optimize data models to ensure adaptability to changes in source data and business requirements.
- Develop machine learning models for forecasting and optimizing business processes.
- Utilize Python (Pandas, PySpark, NumPy, scikit-learn) and SQL (T-SQL, PostgreSQL, PSQL) to manipulate, clean, and analyze data.
- Work with Snowflake and other cloud-based data warehouses to build robust data architectures.
- Implement data governance, security, and compliance standards across data platforms.
- Collaborate with cross-functional teams including data scientists, analysts, and software engineers to support data-driven decision-making.
- Monitor, troubleshoot, and improve data ingestion, transformation, and storage performance.
- Leverage Google Analytics and other cloud-based tools to drive insights and optimize data flows.
Required Skills and Qualifications
- 12 years of experience in data engineering with a focus on cloud data platforms.
- Strong expertise in Google Cloud Storage, Cloud SQL, BigQuery, and Snowflake.
- Advanced proficiency in Python (Pandas, PySpark, NumPy, scikit-learn) for data processing and automation.
- Strong hands-on experience with SQL (T-SQL, PostgreSQL, PSQL) for data querying, transformation, and modeling.
- Design, implement, and manage MongoDB architecture, including configuration, upgrades, scaling, and troubleshooting.
- Knowledge of data architecture, data governance, and security best practices.
- Hands-on experience in building, optimizing, and maintaining data pipelines and ETL processes.
- Experience with machine learning model development for forecasting and data-driven optimizations.
- Solid understanding of cloud computing platforms like Google Cloud Platform, AWS, or Azure.
- Strong analytical and problem-solving skills with a focus on data quality and performance tuning.
- Ability to work in an agile environment, collaborating with multiple stakeholders across teams.
Preferred Skills
- Experience with Google Analytics and its integration with data pipelines.
- Familiarity with orchestration tools like Apache Airflow or Cloud Composer.
- Experience working with Redshift or other cloud-based data warehouse solutions.
- Exposure to CI/CD pipelines for data engineering workflows.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
