Senior Data Engineer
New
US based team members, 6 hours overlap with 8 am - 5 pm Pacific TimeFull-TimeSenior
Salary117,725 - 162,900 USD per year
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Job Details
- Experience
- 3+ years
- Required Skills
- AWSPostgreSQLPythonSQLETLMySQLSnowflakeGoScalaData modeling
Requirements
- Bachelor’s or Master’s degree in Computer Science, Information Technology, Mathematics, or a related field
- 3+ years of experience in data engineering within a modern technology stack, software engineering with data warehousing experience, or data science with data infrastructure experience
- Deep Expertise in functional programming languages such as Python, Go, or Scala
- Strong experience working with big data technologies and distributed systems
- Proficiency in SQL, with experience across relational databases (e.g., PostgreSQL, MySQL)
- Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud
- Familiarity with data warehousing solutions like Redshift, BigQuery, or Snowflake
- Knowledge of data modeling, data architecture, and data governance principles
- Excellent problem-solving skills with strong attention to detail
- Strong communication and collaboration skills, with the ability to work effectively across teams
Responsibilities
- Design, build, and maintain scalable data pipelines and ETL processes to enable reliable data integration and analytics
- Architect and implement robust data storage solutions, including data warehouses, data lakes, and databases
- Partner closely with AI engineers, data analysts, and other cross-functional stakeholders to understand data requirements and deliver solutions that meet business needs
- Optimize and tune data systems to ensure high performance, reliability, and scalability
- Ensure data quality, accuracy, and integrity through rigorous testing, validation, and monitoring
- Establish, document, and enforce data governance standards and best practices
- Stay current on emerging data technologies and industry trends, and evaluate their applicability to our data platform
- Troubleshoot and resolve data-related issues efficiently to minimize disruption and maintain trust in our data systems
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