Senior Data Engineer - Data Warehousing
Summary
A Senior Data Engineer designs, builds, and maintains scalable data pipelines and ETL/ELT processes for the client's data warehouse, ensuring data quality and performance for analytics. Core tech includes SQL (PostgreSQL/MySQL/SQL Server), Python, and big data/cloud platforms like Spark, Hadoop, Snowflake, and BigQuery, working remotely.
About the Role
Our client is seeking a highly motivated Senior Data Engineer to join their remote team and lead the development of their data warehousing solutions. In this role, you will be responsible for designing, building, and optimizing robust data pipelines and ETL processes that power analytics and business intelligence initiatives. You will work with a collaborative team to ensure data quality, accessibility, and efficiency, playing a key part in enabling data-driven decision-making across the organization. This is an excellent opportunity to leverage your expertise in data architecture and big data technologies from anywhere.
Key Responsibilities
- Design, build, and maintain scalable data pipelines and ETL/ELT processes using modern data integration tools.
- Develop and optimize complex SQL queries and stored procedures for data extraction, transformation, and loading.
- Manage and enhance the organization's data warehouse infrastructure, ensuring data integrity and performance.
- Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver solutions.
- Implement data quality checks and monitoring systems to ensure the accuracy and reliability of data assets.
- Stay current with emerging data technologies and best practices to continuously improve data infrastructure.
Requirements
- Bachelor's degree in Computer Science, Engineering, or a related field.
- 5+ years of experience in data engineering or a similar role, with a strong focus on data warehousing.
- Proficiency in SQL and experience with relational databases such as PostgreSQL , MySQL , or SQL Server .
- Hands-on experience with big data technologies like Spark , Hadoop, or cloud-based data platforms (e.g., Snowflake, BigQuery).
- Experience with ETL/ELT tools and programming languages like Python for data manipulation.
- Strong understanding of data modeling, dimensional modeling, and data architecture principles.
Benefits
- Competitive salary and performance-based bonuses.
- Comprehensive health, dental, and vision insurance.
- Generous paid time off and flexible working hours.
- Remote work arrangement allowing for work-life balance.
- Professional development opportunities, including training and conference attendance.