Data Engineer
New
E
Element SolutionsData engineering
Must live in the Continental US.Full-TimeMiddle
Salary95,000 - 106,000 USD per year
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Job Details
- Experience
- At least 3 years of professional experience in data engineering, data integration, ETL/ELT development, or a related technical field. At least 3 years of hands-on experience with Snowflake and Apache Airflow in data engineering or data pipeline development.
- Required Skills
- PythonSQLApache AirflowGitSnowflakeCI/CDData modeling
Requirements
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or an associate degree plus two years' experience.
- At least 3 years of professional experience in data engineering, data integration, ETL/ELT development, or a related technical field.
- At least 3 years of hands-on experience with Snowflake and Apache Airflow in data engineering or data pipeline development.
- Strong proficiency in SQL, including query development, data transformation, and performance optimization.
- Experience developing, scheduling, monitoring, and troubleshooting data pipelines using Apache Airflow.
- Experience designing and maintaining data structures, transformations, and workflows in Snowflake.
- Proficiency in Python or a comparable scripting language for automation and data processing.
- Understanding of relational databases, data modeling, data integration patterns, and data quality practices.
- Experience with version control tools such as Git and collaborative software development practices.
- Experience supporting government contracting, healthcare CMS, health industry, or other regulated environments is preferred.
- Experience with AWS, Microsoft Azure, or Google Cloud Platform is preferred.
Responsibilities
- Design, build, and maintain reliable, scalable ETL/ELT pipelines for ingesting, transforming, and delivering data.
- Develop Apache Airflow DAGs to orchestrate pipeline tasks, schedules, dependencies, and data-processing workflows.
- Integrate data from databases, APIs, and files, applying transformations and preserving data consistency.
- Develop SQL transformations and Snowflake database structures, including schemas, tables, and views.
- Optimize SQL queries and Snowflake workloads by evaluating query performance, warehouse sizing, utilization, and cost.
- Monitor workflow runs, investigate failures, and implement corrective actions, alerts, and operational logging.
- Develop Python scripts and automation to support pipeline operations.
- Develop and maintain automated data validation checks and tests, and investigate data-quality issues.
- Document data lineage, transformation logic, workflow dependencies, recovery steps, and troubleshooting guidance.
- Collaborate with technical teams and stakeholders, participate in code reviews and design discussions, and contribute to version control, automated testing, and CI/CD practices.
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