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Data Pipeline Architect
2 weeks ago
As a skilled professional in data engineering, you will play a pivotal role in helping organizations achieve operational excellence and growth.
A key focus area for this role will be the conceptualization and ownership of problem-solving data marts for consumption by data science and BI teams. This will involve evaluating design and operational tradeoffs within systems to ensure seamless integration and efficient data management.
The ideal candidate will have experience with designing robust data pipelines and ETL processes using data platforms for centralized data warehousing. Additionally, expertise in creating or contributing to frameworks that improve logging data efficacy, while working collaboratively with Engineering teams to troubleshoot issues and resolve them efficiently.
Some of the key responsibilities include validating data integrity throughout the collection process through data profiling to identify and comprehend data anomalies. Furthermore, influencing product and cross-functional teams (engineering, data science, operations, strategy) to identify data opportunities that drive business impact.
Required skills and qualifications:
Experience & Education- Bachelor's degree in Computer Science, Mathematics, or a related field, or equivalent practical experience.
- 5+ years of experience coding with SQL or one or more programming languages (e.g., Python, Java, R, etc.) for data manipulation, analysis, and automation.
- 5+ years of experience designing data pipelines (ETL) and dimensional data modeling for synchronous and asynchronous system integration and implementation.
- Experience in managing troubleshooting technical issues and collaborating with Engineering and Sales Services teams.
Preferred qualifications:
- Master's degree in Engineering, Computer Science, Business, or a related field.
- Experience with cloud-based services relevant to data engineering, data storage, data processing, data warehousing, real-time streaming, and serverless computing.
- Experience with experimentation infrastructure and measurement approaches in a technology platform.
- Experience with data processing software (e.g., Hadoop, Spark) and algorithms (e.g., MapReduce, Flume).
This is an excellent opportunity for individuals seeking to leverage their technical expertise and contribute to driving business results. We are committed to fostering a collaborative environment where professionals can thrive and grow.
