Senior Software Engineer, Data Engineering
Builds and scales ETL pipelines, designs data schemas, and owns data quality/governance for 10x growth. Requires 5+ years in data pipelines with SQL, Spark, Airflow, Python, and MPP databases like Snowflake/Redshift.
About the job
Responsibilities
- Be a hands-on data engineer, building, scaling and optimizing ETL pipelines
- Design data schemas and scale them for 10x data growth
- Ownership of all aspects of data - data quality, data governance, schema design, data quality and security
- Develop scalable data architecture and standardized data models that enable self-serve data insights using AI
- Own the ETL workflows and make sure the pipeline meets data quality and availability requirements
- Work closely with partner teams, like Data Science, Analytics and DevOps
Requirements
- 5+ years experience transforming data to governed and lucid datasets
- 5+ years of hands-on experience to build and deploy production-quality data pipelines
- 5+ years of experience working with stakeholders to provide business insights
- 5+ years of experience writing SQL, Spark, AWS Glue, EMR, Airflow, Python
- 3+ years of hands-on experience using any MPP database system like Snowflake, AWS Redshift or Teradata
- Track record of successful partnerships with Analytics, Data Science and DevOps teams
- Understanding of key metrics for data pipelines and has built solutions to provide visibility to partner teams
Note: Engineers are required to participate in on-call rotation.
Compensation
Base salary: $164,000 - $227,000, plus bonus, equity, and benefits.
Skills
SQL, Spark, Aws Glue, Emr, Airflow, Python, Snowflake, Aws Redshift, Teradata, ETL
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