Senior Data Analytics Engineer
New
United StatesFull-TimeSenior
Salary100,000 - 140,000 USD per year
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Job Details
- Experience
- 4+ years
- Required Skills
- AWSPostgreSQLPythonSQLApache AirflowGCPGitJavaMySQLSnowflakeAzureBigQuerydbtRedshift
Requirements
- 4+ years of experience in data engineering, analytics engineering, or a similar data-focused role.
- Strong proficiency in SQL and experience working with relational databases such as PostgreSQL or MySQL.
- Hands-on experience with cloud data platforms such as AWS, Google Cloud, or Azure, and data warehousing solutions like Snowflake, Redshift, or BigQuery.
- Experience with ETL development tools and frameworks such as Apache Airflow and dbt.
- Solid understanding of data modeling concepts and modern data warehouse architecture.
- Proficiency in at least one programming language such as Python or Java.
- Experience with data quality testing frameworks and validation methodologies.
- Strong analytical and problem-solving skills with attention to detail and data accuracy.
- Good communication skills with the ability to collaborate effectively across technical and non-technical teams.
- Experience using Git for version control and collaborative development workflows.
Responsibilities
- Design, build, and maintain scalable ETL pipelines that integrate data from multiple sources into centralized data warehouse systems supporting analytics and reporting needs.
- Develop and optimize data models and analytical structures to ensure accurate, efficient, and accessible reporting across business functions.
- Collaborate closely with data scientists and engineers to support the deployment and operationalization of machine learning models and analytical solutions.
- Monitor, validate, and improve data quality by identifying inconsistencies, resolving integrity issues, and implementing robust data testing practices.
- Translate business and stakeholder requirements into technical data solutions that support decision-making and operational efficiency.
- Contribute to the development of data documentation, metadata standards, and governance practices to improve data usability and transparency.
- Evaluate and support the implementation of modern data tools and technologies to enhance the data ecosystem.
- Participate in code reviews and help define best practices for data engineering and analytics development.
- Manage assigned projects independently, ensuring timely delivery of high-quality analytical outputs.
- Continuously identify opportunities to improve data workflows, infrastructure, and analytical performance.
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